This PDF file contains the front matter associated with SPIE Proceedings Volume 8668, including the Title Page, Copyright information, Table of Contents, and the Conference Committee listing.

The purpose of our study is to demonstrate the effectiveness of using smartphones for measuring ionizing radiation and to combine the findings with radiation exposure from medical imaging procedures for recording individual annual/lifetime radiation dose and provide improved radiation protection. We developed an application for smartphones which can use the properties of the video camera chip in such smartphones together with highly sufficient statistical evaluation of the signals to detect ionizing radiation. We could show that this application can be used in a large range of dose rates from natural backgrounds to high dose rate pulsed radiation like in fluoroscopic radiation or CT investigations. We could also show that these kinds of systems might help to provide better radiation protection by advising medical staff to use radiation protection material in best dose saving ways.

Physical phantoms are essential for the development, optimization, and clinical evaluation of x-ray systems. These phantoms are used for various tests such as quality assurance testing, system characterization, reconstruction evaluation, and dosimetry. They should ideally be capable of serving as ground truth for purposes such as virtual clinical trials. Currently, there is no anthropomorphic 3D physical phantom commercially available. We present our development of a new suite of physical breast phantoms based on real patient data. The phantoms were generated from the NURBS-based extended cardiac-torso (XCAT) breast phantoms, which were segmented from patient dedicated breast computed tomography data. High-resolution multi-material 3D printing technology was used to fabricate the physical models. Glandular tissue and skin were presented by the most radiographically dense photopolymer available to the printer, mimicking a 75% glandular tissue. Adipose tissue was presented by the least radiographically dense photopolymer, mimicking a 35% glandular tissue. The glandular equivalency was measured by comparing x-ray images of samples of the photopolymers available to the printer with those of breast tissue-equivalent materials. The mammographic projections and tomosynthesis reconstructed images of fabricated models showed great improvement over available phantoms, presenting a more realistic breast background.

The detectors that are used for endovascular image-guided interventions (EIGI), particularly for neurovascular interventions, do not provide clinicians with adequate visualization to ensure the best possible treatment outcomes. Developing an improved x-ray imaging detector requires the determination of estimated clinical x-ray entrance exposures to the detector. The range of exposures to the detector in clinical studies was found for the three modes of operation: fluoroscopic mode, high frame-rate digital angiographic mode (HD fluoroscopic mode), and DSA mode. Using these estimated detector exposure ranges and available CMOS detector technical specifications, design requirements were developed to pursue a quantum limited, high resolution, dynamic x-ray detector based on a CMOS sensor with 50 μm pixel size. For the proposed MAF-CMOS, the estimated charge collected within the full exposure range was found to be within the estimated full well capacity of the pixels. Expected instrumentation noise for the proposed detector was estimated to be 50-1,300 electrons. Adding a gain stage such as a light image intensifier would minimize the effect of the estimated instrumentation noise on total image noise but may not be necessary to ensure quantum limited detector operation at low exposure levels. A recursive temporal filter may decrease the effective total noise by 2 to 3 times, allowing for the improved signal to noise ratios at the lowest estimated exposures despite consequent loss in temporal resolution. This work can serve as a guide for further development of dynamic x-ray imaging prototypes or improvements for existing dynamic x-ray imaging systems.

The multi-resolution technology was developed for dynamic flat panel detectors for X-ray imaging. This multi-resolution technology allows us to switch between the 1 x 1 mode (150 μm square) and the 2 x 2 mode (300 μm square) instantaneously, using an external control. We developed a 17" x 17" dynamic detector using this multi-resolution technology. This novel dynamic detector has a high sensitivity and a high-speed readout and it can reduce the radiation exposure dose and deliver a smooth image. The key feature of our multi-resolution technology is capable of reading 4 pixel signals simultaneously. The sensitivity and the readout speed in the 2 x 2 mode were 4 times higher than those in the 1 x 1 mode. The multi-resolution technology was implemented using a unique thin film transistor structure; that is, one pixel has two switches, each of which are turned on/off depending on the readout mode. As a result, the dynamic detector with a large active area of 17" x 17" realized a high detective quantum efficiency value of 40% under the low radiation of RQA5 20 nGy and a high-speed readout of 30 frames/sec. This multi-resolution technology made it possible to reduce the radiation exposure dose in a variety of applications.

Field emission electron sources have been increasingly investigated and practiced as cold electron sources for many Xray generation mechanisms especially in certain medical imaging applications, such as computed tomography (CT). In a field emission electron source, the emission current and cathode life are the two key performance parameters of interests. Conventional field emission electron source in the form of a 2-dimensional single surface cathode design is often undergoing the bottleneck of limited emission current. Higher current can be obtained by increasing the strength of driving electric field. However this is at the expense of a reduced cathode life. In this paper we present a novel field emission electron source design based on a 3-dimensional semi-enclosed cavity structure, by utilizing the cavity’s multiple inner faces as electron emission surfaces. The cavity has one bottom inner face open for electron ejection, the area of which was kept the same as a conventional single surface cathode to maintain the same initial electron beam cross section. The extended emission area of the new cathode design due to its 3-dimensional structure provides a higher electron emission current while maintaining the same beam cross section, resulting in an improved effective emission current density. We have demonstrated a significantly increased electron emission current from this 3-dimensional cathode under a constant electric field, without over-driving the cathode field emitters. Alternatively this new cathode design can also achieve the same total emission current with a lower electric field compared with a conventional 2- dimensional cathode, which will significantly extend its life.

Preclinical imaging is a cornerstone of translational research, as all therapeutic drugs need to be tested for efficacy and toxicity on animals prior to human trials. Optical imaging techniques, such as bioluminescence and multispectral fluorescence imaging, currently dominate preclinical functional imaging despite their depth dependent limitations on quantitation and sensitivity. Translating drugs developed with these techniques to clinical models can therefore be difficult. Hence, clinically relevant nuclear imaging techniques, such as SPECT and PET, are therefore becoming increasingly used in preclinical imaging. Dedicated preclinical SPECT and PET systems are now available, but for many preclinical research groups this requires a significant investment in new equipment.

Active matrix flat-panel imagers (AMFPIs) have become ubiquitous in medical imaging environments. AMFPIs are based on two-dimensional pixelated arrays coupled to various x-ray converter materials that provide either indirect or direct detection of the incident x-ray radiation. However, the capabilities of this technology are severely constrained by the underlying solid-state properties of the amorphous silicon semiconductor material employed in the thin-film transistors present in each array pixel. The considerably higher electron and hole mobilities of polycrystalline silicon, a semiconductor material that (like amorphous silicon) is well suited to fabrication of transistors for large area electronics, provide the potential to overcome these constraints by increasing the overall gain of the system relative to the electronic additive noise. To explore this potential, a series of prototype arrays based on increasingly complex pixel designs employing polycrystalline silicon transistors is under development by our collaboration. The designs include several generations of active pixel arrays that incorporate sophisticated pixel-level amplifier circuits with the goal of improving imaging performance. In this paper, an initial analysis of the noise and DQE performance of selected prototype pixel circuit designs will be presented. The results are based on a combination of Monte Carlo -based circuit simulations and cascaded systems analysis, supplemented with information obtained from measurements performed on poly-Si transistors. The paper concludes with a brief discussion of the potential for, and challenges associated with, the creation of single photon counting arrays based on poly-Si TFTs.

In this work, we demonstrate the ability to determine the material composition of a sample by measuring coherent scatter diffraction patterns generated using a coded-aperture x-ray scatter imaging (CAXSI) system. Most materials are known to exhibit unique diffraction patterns through coherent scattering of low-energy x-rays. However, clinical x-ray imagers typically discard scatter radiation as noise that degrades image quality. Through the addition of a coded aperture, the system can be sensitized to coherent scattered photons that carry information about the identity and location of the scattering material. In this work, we demonstrate this process using a Monte-Carlo simulation of a CAXSI system. A simulation of a CAXSI system was developed in GEANT4 with modified physics libraries to model coherent scatter diffraction patterns in materials. Simulated images were generated from 10 materials including plastics, hydrocarbons, and biological tissue. The materials were irradiated using collimated pencil- and fan-beams with energies of 160 kVp. The diffraction patterns were imaged using a simulated 2D detector and mathematically deconstructed using an analytical projection model that accounted for the known x-ray source spectrum. The deconstructed diffraction patterns were then matched with a library of known coherent scatter form-factors of different materials to determine the identity of the scatterer at different locations in the object. The results showed good agreement between the measured and known scatter patterns from the materials, demonstrating the ability to image and identify materials at different 3D locations within an object using a projection-based CAXSI system.

Individual projection images in Digital Breast Tomosynthesis (DBT) must be acquired with low levels of radiation, which significantly increases image noise. This work investigates the influence of a denoising algorithm and the Anscombe transformation on the reduction of quantum noise in DBT images. The Anscombe transformation is a variance-stabilizing transformation that converts the signal-dependent quantum noise to an approximately signalindependent Gaussian additive noise. Thus, this transformation allows for the use of conventional denoising algorithms, designed for additive Gaussian noise, on the reduction of quantum noise, by working on the image in the Anscombe domain. In this work, denoising was performed by an adaptive Wiener filter, previously developed for 2D mammography, which was applied to a set of synthetic DBT images generated using a 3D anthropomorphic software breast phantom. Ideal images without noise were also generated in order to provide a ground-truth reference. Denoising was applied separately to DBT projections and to the reconstructed slices. The relative improvement in image quality was assessed using objective image quality metrics, such as peak signal-to-noise ratio (PSNR) and mean structural similarity index (SSIM). Results suggest that denoising works better for tomosynthesis when using the Anscombe transformation and when denoising was applied to each projection image before reconstruction; in this case, an average increase of 9.1 dB in PSNR and 58.3% in SSIM measurements was observed. No significant improvement was observed by using the Anscombe transformation when denoising was applied to reconstructed images, suggesting that the reconstruction algorithm modifies the noise properties of the DBT images.

Digital breast tomosynthesis (DBT) has been investigated as a promising alternative to conventional X-ray mammography for breast cancer screening. By reconstructing 3D volumetric images from multiple 2D projections measured over a limited angular range, it can offer depth-directional information and improve both sensitivity and specificity of cancer detection in dense breasts. The diagnostic performance of DBT can be affected by a number of imaging parameters. The angular range of scan orbit is one of the most crucial factors, since it determines the depth-directional resolution. Recently, we proposed the wide angle tomosynthesis based on voltage modulations of X-ray source. By using X-rays with large penetration power on exterior positions, it can acquire high-SNR projections over a wide angular range. In this paper, we present comparative studies on exposure conditions in DBT, including narrow and wide angle scan using an invariant tube voltage of X-ray source, and wide angle scan with the voltage modulation technique. In addition, we compared the conventional reconstruction methods with recently proposed IDIR algorithms. In preliminary studies, the wide-angle scheme with proposed IDIR algorithm showed superior performances in detecting abnormal lesions over conventional approaches.

Chest tomosynthesis is an imaging modality that provides 3D sectional information of a patients thoracic cavity using limited angle x-ray projections. Studies show that tomosynthesis can improve the detection of subtle lung nodules comparing to conventional radiography at a lower radiation dose than CT. In the conventional design, the projection images are collected by mechanically moving a single x-ray source to different viewing angles. We investigated the feasibility of stationary chest tomosynthesis using the distributed CNT x-ray source array technology, which can generate a scanning x-ray beam without any mechanical motion. A proof-of-concept system was constructed using a short linear source array and a at panel detector. The performance of the source including the flux was evaluated in the context of chest imaging. The bench-top system was characterized and images of a chest phantom were acquired and reconstructed. The preliminary results demonstrate the feasibility of stationary chest tomosynthesis using the CNT x-ray source array technology.

In digital breast tomosynthesis (DBT), a 3D image of the breast is generated from x-ray projections at various angles. There are two mechanisms for acquiring projection images in DBT, step-and-shoot motion and continuous tube motion. The benefit of continuous tube motion is shorter scan time and hence less patient motion; the trade-off is focal spot blurring. To minimize focal spot blurring in a system with continuous tube motion, this study proposes a new velocity profile for the x-ray tube during the scan. Unlike existing systems for which the x-ray tube has constant angular velocity, we investigate a smoothly-varying tube velocity that approaches zero during each projection and is larger between projections. With this unique design, the filtered backprojection reconstruction of a sinusoidal test object was calculated, and modulation was determined at various frequencies. It is shown that the newly proposed tube velocity yields increased modulation in the reconstruction relative to a conventional system with continuous tube motion. The modulation in the re-designed system differs minimally from an analogous step-and-shoot system operated with the same scan time. This improvement in image quality was validated with reconstructions of microcalcifications in computer breast phantoms. It is known that continuous tube motion reduces the contrast of microcalcifications relative to stepand-shoot systems; we show that the newly proposed tube motion increases the contrast of microcalcifications compared to conventional continuous tube motion. In conclusion, this work proposes a strategy for optimizing the velocity of tube motion in DBT.

Contrast enhanced (CE) breast imaging has been proposed as a method to increase the sensitivity and specificity of breast cancer detection. Because malignant lesions often exhibit angiogenesis, the uptake of radio-opaque contrast agents (e.g. iodine) results in increased attenuation compared to the background tissue. Both planar CE digital mammography (CE-DM) and digital breast tomosynthesis (CE-DBT) have been proposed, using temporal or dual energy (DE) subtraction to remove tissue backgrounds. In the current study, we apply a cascaded linear systems model approach to analyze CE techniques with DE subtraction for designing a diagnostic imaging study, including the effects of contrast dynamics. We apply the model for both CE-DM and CE-DBT to calculate the ideal observer signal-to-noise ratio (SNR) for the detection of I contrast objects of different sizes and concentrations. The calculation of this figure-of-merit (FOM) was be used to optimize CE clinical imaging protocols.

We have recently developed a method of using a distributed x-ray source array to obtain images with scatter correction for tomographic reconstruction of an object. The method consists of obtaining x-ray images of the object with and without the primary beam sampling apparatus. In this study, we report the results of applying the scatter correction method for breast tomosynthesis imaging using the carbon nanotube x-ray based stationary Digital Breast Tomosynthesis (s-DBT) system developed at UNC. The unique design of s-DBT system makes it possible to estimate the image of the scatter profile of the object with very low dose, and without significant increase in acquisition time. An anthropomorphic breast phantom was used for quantitative analysis of the change in contrast and scatter-to-primary ratio. Our results suggest that the scatter correction method is effective and can be used for enhanced contrast.

In digital breast tomosynthesis (DBT), the reconstructed image quality of small objects such as microcalcifications are limited by the detector resolution and the reconstruction voxel dimensions used, in addition to the inherent in-plane and inter-plane blurring due to limited-angle image acquisition. We are investigating the effects of subpixel reconstruction on the image quality of microcalcifications. In this study, subpixel projection images were generated by polynomial interpolation of the gray level values of the original projection images to reduce the pixel pitch by a factor of 2 to 4. The voxel dimensions in the reconstruction volume were varied. The in-plane voxel dimensions were chosen to match the pitch in the subpixel projection images while the voxel dimension in the depth-direction was varied systematically to study the relative effects. DBT scans of human subjects with microcalcifications were acquired with a GE prototype DBT system at 0.1 mm x 0.1 mm pixel pitch. In addition, computer modeling of the same system was used to generate simulated DBT projections of small spheres as a surrogate for microcalcifications. DBT volumes corresponding to the subpixel projections were reconstructed with SART. The FWHMs of the line profiles of the simulated microcalcifications on their in-focus DBT slices and FWHMs of the inter-plane artifact spread function (ASF) in the depth-direction were used for comparison of reconstruction quality. The results indicated that subpixel reconstruction increased the object contrast and reduced the inter-plane blurring to a certain extent. Further work is underway to study the dependence of the trade-off between image quality and reconstruction voxel dimensions on the image acquisition parameters (total scan angle, angular increment) of the DBT system and the properties of the objects of interest.

Present day treatment for neurovascular pathological conditions involves the use of devices with very small features such as stents, coils, and balloons; hence, these interventional procedures demand high resolution xray imaging under fluoroscopic conditions to provide the capability to guide the deployment of these fine endovascular devices. To address this issue, a high resolution x-ray detector based on EMCCD technology is being developed. The EMCCD field-of-view is enlarged using a fiber-optic taper so that the detector features an effective pixel size of 37 μm giving it a Nyquist frequency of 13.5 lp/mm, which is significantly higher than that of the state of the art Flat Panel Detectors (FPD). Quantitative analysis of the detector, including gain calibration, instrumentation noise equivalent exposure (INEE) and modulation transfer function (MTF) determination, are presented in this work. The gain of the detector is a function of the detector temperature; with the detector cooled to 50 C, the highest relative gain that could be achieved was calculated to be 116 times. At this gain setting, the lowest INEE was measured to be 0.6 μR/frame. The MTF, measured using the edge method, was over 2% up to 7 cycles/ mm. To evaluate the performance of the detector under clinical conditions, an aneurysm model was placed over an anthropomorphic head phantom and a coil was guided into the aneurysm under fluoroscopic guidance using the detector. Image sequences from the procedure are presented demonstrating the high resolution of this SSXII.

The new Solid State X-ray Image Intensifier (SSXII) is a high-resolution, high-sensitivity, real-time region-ofinterest (ROI) x-ray imaging detector. Evaluations were made of both standard linear systems metrics (MTF, DQE) and total system performance with generalized linear systems metrics (GMTF, GDQE) including scatter and geometric un-sharpness for simulated clinical conditions. The SSXII is based on a 1k x 1k EMCCD sensor coupled to a 300 μm thick CsI(Tl) phosphor through a 2.88:1 fiber optic taper resulting in a 37 μm effective pixel size and an effective 3.7 cm x 3.7 cm square field-of-view (FOV). Standard methods were used to calculate MTF, NNPS and DQE. Generalized metrics were calculated and compared for three different magnifications (1.03, 1.11 and 1.2) and three different focal spots (0.3 mm, 0.5 mm and 0.8 mm) for a scatter fraction of 0.28. For an RQA5 spectrum, at 5 cycles/mm the MTF was found to be 0.06 and DQE was 0.04, while the DQE(0) was 0.60. Focal spot un-sharpness and scatter significantly degrades the GMTF and GDQE performance of the detector. A low frequency drop is caused by scatter and is almost independent of focal spot size and magnification. The degradation for middle range frequencies is caused by geometric un-sharpness and increases with focal spot size and magnification. This degradation was least in the case of the small focal spot and almost independent of magnification. In spite of this degradation, the high resolution SSXII with a small FOV may have a significant impact on ROI image-guided neuro-interventions since it demonstrates far better performance than standard current detectors.

Knowledge of the uncertainty associated with Monte Carlo estimates is useful for determining when to stop a simulation run when statistical uctuations fall below a desired tolerance level, and for designing and analyzing variance reduction techniques. In this work, we discuss how to analytically calculate the uncertainty of Monte Carlo variance estimates from higher order moments of the distribution of events. In addition, we show how these expressions can be incorporated in the study of x-ray imaging detectors to manage runtime and precision of the simulation. Our analysis can be used to design variance reduction techniques for Monte Carlo simulations when, as in many cases in imaging, the variance and not the mean, is the quantity of interest.

Software breast phantoms have been developed for use in evaluation of novel breast imaging systems. Software phantoms are flexible allowing the simulation of wide variations in breast anatomy, and provide ground truth for the simulated tissue structures. Different levels of phantom realism are required depending on the intended application. Realistic simulation of dense (fibroglandular) tissue is of particular importance; the properties of dense tissue – breast percent density and the spatial distribution – have been related to the risk of breast cancer. In this work, we have compared two methods for simulation of dense tissue distribution in a software breast phantom previously developed at the University of Pennsylvania. The methods compared are: (1) the previously used Gaussian distribution centered at the phantom nipple point, and (2) the proposed combination of two Beta functions, one modeling the dense tissue distribution along the chest wall-to-nipple direction, and the other modeling the radial distribution in each coronal section of the phantom. Dense tissue distributions obtained using these methods have been compared with distributions reported in the literature estimated from the analysis of breast CT images. Qualitatively, the two methods produced rather similar dense tissue distributions. The simulation based upon the use of Beta functions provides more control over the simulated distributions through the selection of the various Beta function parameters. Both methods showed good agreement to the clinical data, suggesting both provide a high level of realism.

While great advances are made toward making highly realistic, surface models of the human anatomy, very little has been done to fill these bounded surfaces with models of anatomical texture. We propose a method whereby realistic anatomically-based computed tomography (CT) texture can be incorporated into voxelized versions of the 4D extended cardiac-torso (XCAT) phantom. Our source of texture comes from patient CT scans from the Duke CT imaging database. These image-sets were de-noised using anisotropic diffusion. Two organs were selected from which texture was obtained, liver and lungs. From each organ, multiple regions of interest (ROIs) were taken and tiled side-by-side to create a larger image. Textures for the liver and lungs were extrapolated using ImageQuilting, based on the tiled images. Next, a NURBSbased XCAT phantom was voxelized at the same resolution as the textures. The texture was then placed in the voxelized phantoms. Finally, CT simulations of the phantoms with and without the textures were compared against each other, using the power spectral density. This work shows that there is a way whereby the XCAT phantoms can be textured to give more realistic appearance in CT simulations. It is anticipated that this method would find great use in making projections of the XCAT phantom look more realistic and allow for the phantoms to not only be utilized in dosimetrical evaluations, but in image quality studies as well.

We have investigated the multi-energy performance of our most recent prototype CT scanner with CdTe-based counting detector. With its small pixel pitch of 225 μm this device is prepared for the high X-ray fluxes occurring in clinical CT. Each of these pixels is equipped with two adjustable counters. The ASIC architecture of the detector allows configuration of the counter thresholds in chess patterns, enabling data acquisition in up to four energy bins. We have studied the material separation capability of counting CT with respect to potential clinical applications. Therefore we have analyzed contrast and noise properties in material decomposed CT images using up to four base materials. We have studied contrast agents containing iodine, gadolinium, or gold, and the body-like materials calcium, fat, and water. We describe the mathematical framework used in this work and demonstrate the general multi-energy capability of counting CT with simulations and experimental data from our prototype scanner. To prove the clinical relevance of our studies we compare the results to those obtained with well-established dual-kVp techniques recorded at same patient dose and with identical image sharpness.

Photon counting detectors offer some unique features for x-ray imaging. If designed correctly, photon counting detectors have no readout noise and no dark counts. This is an important feature in for example low dose CT imaging where the total dose is distributed over a large number of projections from different angles. In addition to this it is also possible to incorporate pulse height discrimination of each photon event, thus enabling the recording of images from multiple energy intervals in a single exposure. We demonstrate the performance of a newly developed dual-energy fast photon counting detector with 100μm pixel size that can be read out up to 1000fps. It consists of a three side buttable ASIC that is bump bonded to a CdTe converter. The very high conversion efficiency of CdTe makes the detector suitable for a wide range of applications requiring high spatial resolution at low doses. The efficiency of the detector is maintained all the way out to the edge of the chip which opens up the possibility to build larger detectors still fulfilling medical requirements. The novel detector incorporates a charge sharing correction feature and the effect of this function is demonstrated using the DQE measurements for different spectra as well as with spectrum reconstruction from Cd¹⁰⁹ and Am²⁴¹ radioactive sources. We show that this charge sharing correction feature affects the properties of NPS and MTF, and the energy resolution is greatly enhanced. Measurements are also compared to a simulation model for the detector system.

Photon counting detectors are expected to bring along various clinical benefits in CT imaging. Among the benefits of these detectors is their intrinsic spectral sensitivity that allows to resolve the incident X-ray spectrum. Their capability for multi-energy imaging enables material segmentation, but it is also possible to use the spectral information to create fused gray-scale CT images with improved imaging properties. We have developed and investigated an optimization method that maximizes the image contrast-to-noise ratio, making use of the spectral information in data recorded with a counting detector with up to six energy thresholds. The resulting merged gray-scale CT images exhibit significantly improved CNR² for a number of clinically established, potentially novel and hypothetical contrast agents in the thin absorber approximation. In this work we motivate and describe the optimization method, provide the deduced optimal sets of threshold energies and mixing weights, and summarize the maximally achievable gain in CNR² for each contrast agent under study.

Spectral computed tomography (CT) with photon-counting detectors (PCDs) has the potential to substantially advance diagnostic CT imaging by reducing image noise and dose to the patient, by improving contrast and tissue specificity, and by enabling molecular and functional imaging. The current PCD technology, however, is limited by two main factors: imperfect energy measurement (spectral response effects, SRE) and limited count rate (pulse-pileup effects, PPE, due to detector dead-times). The overall goal of our research is to develop compensation algorithms for these sources of data distortions, to demonstrate that PCDs are suitable for clinical CT, and to identify key clinical applications for spectral CT with PCDs. We have already developed an iterative compensation scheme that includes a forward projection model of the imaging chain and that can compensate for either SRE or PPE distortions separately by maximizing a penalized log-likelihood function. In this paper we describe the evaluation of a combined, cascaded SRE and PPE model for PCDs and compare the models to data acquired with an experimental table-top PCD-CT system. The separation into count-rate independent effects (SRE) and count-rate dependent effects (PPE) allows cascading the forward model. First, the SRE model is evaluated using low count rates. Then the PPE model is cascaded and the combined SRE+PPE model is evaluated. Several different attenuators were used, including K-edge materials and the models and data were compared for various count-rate conditions.

Single-photon counting (SPC) x-ray imaging has the potential to improve image quality and enable new advanced energy-dependent methods. Recently, cascaded systems analysis (CSA) has been extended to the description of the detective quantum efficiency (DQE) of SPC detectors. In this article we apply the new CSA approach to the description of the DQE of hypothetical direct-conversion selenium (Sc) and cadmium zinc telluride (CdZnTc) detectors including the effects of poly-energetic x-ray spectra, stochastic conversion of x-ray energy to electron­ hole (c-h) pairs, depth-dependent collection of e-h pairs using the Hecht relation, additive electronic noise, and thresholding. Comparisons arc made to an energy-integrating model. For this simple model, with the exception of thick (1- 10 mm) Sc-bascd convertors, we found that the SPC DQE was 5-20 %greater than that of the energy­ integrating model. This trend was tnw even when additive noise was included in the SPC model and excluded from the energy-integrating model. However, the DQE of SPC detectors with poor collection efficiency (such as thick (<1 mm) Sc detectors) and high levels of additive noise can be degraded by 40-90 % for all energies and x-ray spectra considered. vVhile photon-counting approaches arc not yet ready for routine diagnostic imaging, the available DQE is equal to or higher than that of conventional energy-integrating detectors under a wide range of x-ray energies and convertor thickness. However, like energy-integrating detectors, the DQE of SPC detectors will be degraded by the combination of poor collection efficiency and high levels of additive noise.

Semiconductor based photon-counting detectors for x-ray CT have a number of advantages over energy integrat­ ing detectors, including reduced electronic and Swank noise, increased dynamic range, capability of spectral CT for material decomposition, and improved SNR characteristics through energy weighting. Quite a few clinical applications could benefit from high-resolution spectral CT. For example, in breast CT the visualization of mi­ crocalcifications and assessment of tumor microvasculature after contrast enhancement require spatial resolution on the order of 100 μm or better. A straightforward approach to increasing spatial resolution by decreasing the detector pixel size, leads to two major problems: 1) fabricating circuitry with small pixels becomes very costly, and 2) inter-pixel charge spreading can obviate any improvement in spatial resolution. In this study, we have used computer simulations to investigate position estimation algorithms that utilize charge sharing to achieve sub-pixel position resolution. To study these algorithms, we model a simple detector geometry with a pixellated 5 x 5 anode array, and use conditional probability functions modeling electron-hole charge transport in CZT. We used COMSOL Multiphysics software to map the distribution of charge pulses in the detector. Performance of two x-ray interaction position estimation algorithms were evaluated: 1) method of maximum likelihood, and 2) a fast, practical algorithm that can be realistically implemented in a readout ASIC, providing identification of the quadrant of the pixel in which interaction occurred. Both methods exhibit good sub-pixel resolution performance, however their actual efficiency is limited by electronic noise.

We have developed dual energy (DE) iodine contrast imaging functions with a commercial mammography and tomosynthesis system. Our system uses a tungsten target x-ray tube and selenium direct conversion detector. Conventional low energy (LE) images were acquired with existing Rh, Ag and Al filters at the screening doses while the high energy images (HE) were acquired with new Cu filters at half of the screening doses. In DE 2D mode, a pair of LE and HE images was taken with one second delay time between and with anti-scatter grid. In DE 3D mode, 22 views of alternating LE and HE were taken over 15 degrees angle in seven seconds without grid while tube was scanned continuously. We used log-subtraction algorithm to obtain clean DE images with the subtraction factor K derived empirically. In 3D mode, the subtraction was applied to each pair of LE and HE slices after reconstruction. The x-ray technique optimization was done with simulation and phantom study. We performed both phantom and patient studies to demonstrate the advantage of iodine contrast imaging. Among several new things in our work, a selenium detector optimized for DE imaging was tested and a large dose advantage was demonstrated; 2D and 3D DE images of a breast under same compression were acquired with a unique DE combo mode of the system, allowing direct image quality comparison between 2D and 3D modes. Our study showed that new DE system achieved good image quality. DE imaging is be a promising modality to detect breast cancer.

Stationary Digital Breast Tomosynthesis (s-DBT) is a carbon nanotube based breast imaging device with fast image acquisition and decent resolution. In this paper, we investigate several representative reconstruction methods with the recently improved s-DBT system and also introduce a two-step reconstruction strategy with Pre-computed Backprojection based penalized-likelihood (PPL). This strategy reconstructs three dimensional (3-D) images with a desired resolution properties by choosing the corresponding smoothing parameter, which is evaluated in advance by studying simulated data. Our experiments show that the current s-DBT system has been greatly improved with respect to the performance of image reconstructions. PPL method exhibits controllable pixel precision, high image contrast and low noise on reconstructed images. Therefore, the enhanced Contrast Noise Ratio (CNR) from PPL method benefits both micro-calcifications and mass of the breast-equivalent phantom.

A new algorithm is suggested to compute one or several virtual projection images directly from cone-beam data acquired in a tomosynthesis geometry. One main feature of this algorithm is that it does not involve the explicit reconstruction of a 3D volume, and a subsequent forward-projection operation, but rather operates using solely 2D image processing steps. The required 2D processing is furthermore based on the use of pre-computed entities, so that a significant speed-up in the computations can be obtained. The presented algorithm can be applied to a variety of CT geometries, and is here investigated for a mammography application, to simulate virtual mammograms from a set of low-dose tomosynthesis projection images. A first evaluation from real measured data is given.

We are investigating human-observer models that perform clinically realistic detection and localization tasks as a means of making reliable assessments of digital breast tomosynthesis images. The channelized non-prewhitening (CNPW) observer uses the background known exactly task for localization and detection. Visual-search observer models attempt to replicate the search patterns of trained radiologists. The visual-search observer described in this paper utilizes a two-phase approach, with an initial holistic search followed by directed analysis and decision making. Gradient template matching is used for the holistic search, and the CNPW observer is used for analysis and decision making. Spherical masses were embedded into anthropomorphic breast phantoms, and simulated projections were made using ray-tracing and a serial cascade model. A localization ROC study was performed on these images using the visual-search model observer and the CNPW observer. Observer performance from the two computer observers was compared to human observer performance. The visual-search observer was able to produce area under the LROC curve values similar to those from human observers; however, more research is needed to increase the robustness of the algorithm.

Digital breast tomosynthesis (DBT) is suggested to have superior performance compared to 2D mammography in terms of cancer visibility, especially in the case of dense breasts. However, the overall performance of tomosynthesis for screening applications, and the manner in which tomosynthesis should be optimally used for screening remains unclear. This motivates the development of software tools that can insert user-defined synthetic pathology of realistic appearance into clinical tomosynthesis images for subsequent use in virtual clinical trials. We present a method for inserting lesions grown using Diffusion Limited Aggregation, previously validated in 2D mammograms, into clinical DBT images. A preliminary pilot study was used to validate the realism of the masses, wherein three readers each viewed 19 cases and rated the realism of the inserted masses. Each case included a simulated mass inserted in the tomosynthesis projections and the counterpart digital 2D mammogram. These results show that masses can be successfully embedded in the tomosynthesis projections and can produce visually authentic DBT images containing synthetic pathology. These results will be used to further optimize the appearance of these masses in DBT for an upcoming validation.

Dark-field imaging has the potential to overcome limitations in computed tomography (CT) investigating relatively weakly absorbing material. However, an object-position dependence of the visibility loss in dark-field imaging is observed. This effect might be negligible for small objects, but, for acquisition geometries using fanangle apertures and field of views as those in human CT scanners, the object-position dependence of visibility loss has to be taken into consideration if the scattering structure within the object is in the range of the grating periods, i.e. micrometer. This work examines the effect of object-position dependent visibility loss in dark-field imaging experimentally, investigates its consequences and presents an algorithm which solves the corresponding reconstruction problem.

Grating-based X-ray phase-contrast imaging (XPCI) is a promising modality to increase soft-tissue contrast in medical imaging and especially in the case of mammography. Several groups worldwide have performed investigations on grating-based Talbot-Lau X-ray imaging of breast tissue, but in most cases focussed on the soft tissue contrast enhancement of the differential phase image. In this contribution, we present promising measurements with a Talbot-Lau interferometer of several mas­tectomy breast tissue samples especially focussed on the sensitivity of the dark-field signal of microcalcifications and with a comparable dose value to conventional mammography. We can present a contrast improvement for calcifications in surrounding breast tissue for the dark-field image by a factor of 10 related to the attenuation image.

Although the relative ease of implementation and compact nature of grating-based differential phase contrast CT (DPC-CT) has sparked tremendous enthusiasm for potential medical applications, the pros and cons of this imaging method remains to be addressed before an actual clinical system can be constructed. To address these unknowns, either numerical simulations or direct hardware implementations can be used. However, both approaches have their limitations. It is highly desirable to develop a research method to enable imaging performance prediction for a future DPC-CT system from the performance of an available absorption CT (ACT) system. In this paper, a theoretical framework was developed to accurately predict the noise properties and detection performance of DPC-CT from that of conventional ACT. The framework was derived based on a fundamental noise relationship between DPC-CT and ACT and was experimentally validated. An example has been given in the paper on how the framework can be utilized to predict model observer detectability index of a DPC breast CT constructed based on an existing absorption breast CT. This framework is expected to become a valuable tool in addressing the following questions: (i) With a fixed radiation dose in a particular clinical application, how well can a specific detection/discrimination imaging task can be performed provided that an existing ACT scanner is modified into a DPC-CT by inserting a grating interferometer, which is characterized by a few design parameters (e.g., pitches and duty cycles of the gratings, relative distance between the gratings, etc.) into the ACT system? (ii) If a DPC-CT system can outperform an ACT for certain detection/discrimination tasks under the constraint of identical radiation dose to the image object, how would one optimize design parameters of the gratings in order to maximize its potential clinical benefits?

The edge illumination principle was first proposed at Elettra (Italy) in the late nineties, as an alternative method for achieving high phase sensitivity with a very simple and flexible set-up, and has since been under continuous development in the radiation physics group at UCL. Edge illumination allows overcoming most of the limitations of other phase-contrast techniques, enabling their translation into a laboratory environment. It is relatively insensitive to mechanical and thermal instabilities and it can be adapted to the divergent and polychromatic beams provided by X-ray tubes. This method has been demonstrated to work efficiently with source sizes up to 100m, compatible with state-of-the-art mammography sources. Two full prototypes have been built and are operational at UCL. Recent activity focused on applications such as breast and cartilage imaging, homeland security and detection of defects in composite materials. New methods such as phase retrieval, tomosynthesis and computed tomography algorithms are currently being theoretically and experimentally investigated. These results strongly indicate the technique as an extremely powerful and versatile tool for X-ray imaging in a wide range of applications.

Today’s commercial X-ray micro computed tomography (CT) specimen systems are based on microfocus sources, 2D pixel array cameras and short source-to-detector distances (i.e. cone-beam configurations). High resolution is achieved by means of geometric magnification. The further development of such devices to acquire phase and scattering contrast images can dramatically enhance their range of applications. Due to the compact geometries, which imply a highly diverging beam, the gratings must be curved to maintain highest imaging performance over a large field of view. We report about the implementation of extremely compact Talbot and Talbot- Lau type grating interferometers which are compatible to the geometry of typical micro CT systems. For the analytical description of the imaging system, formulas are presented describing the dependency of the sensitivity on geometric parameters, camera and source parameters. Further, the imaging pipeline consisting of the data acquisition protocol, radiographic phase retrieval and tomographic image reconstruction is illustrated. The reported methods open the way for an immediate integration of phase and scattering contrast imaging on table top X-ray micro CT scanners.

The Talbot-Lau grating interferometer enables refraction based imaging with conventional X-ray tubes, offering the promise of a new medical imaging modality. The fringe contrast of the normal incidence interferometer is however insufficient at the >40 keV photon energies needed to penetrate thick body parts, because the thin absorption gratings used in the interferometer become transparent. To solve this problem we developed a new interferometer design using gratings at glancing incidence. For instance, using 120 μm thick Au gratings at 10° incidence we increased several fold the interferometer contrast for a spectrum with ~58 keV mean energy. Tests of DPC-CT at 60-80kVp using glancing angle interferometers and medically relevant samples indicate high potential for clinical applications. A practical design for a slot-scan DPC-CT system for the knee is proposed, using glancing angle gratings tiled on a single substrate.

The effects of beam hardening have previously been extended from absorption imaging to phase contrast imaging, showing a similar, albeit reduced, effect in the phase images. The effect of beam hardening on the interferometer performance, however, has not been demonstrated. In this work, the visibility reduction on a differential phase contrast imaging system due to spectral changes as a result of beam hardening is demonstrated. The implication of this reduction is an artificial increase in noise for the phase contrast image through highly-attenuating regions of the object. In addition, false signal will be recorded in the dark-field image, which normally shows only highly-scattering objects and interfaces. The results show that with added beam filtration, the effect is reduced, just as with more traditional beam hardening artifacts. However, the effect also means that one must also take into account the desired imaging task when determining the system’s design energy.

This study investigates the possibility of using the model observer detectability to represent human detection performance in differential phase contrast CT (DPC-CT). Five model observers were investigated, including the prewhitening (PW) observer, the prewhitening observer with eye filter and internal noise (PWEi), the nonprewhitening (NPW) observer, the non-prewhitening observer with eye filter (NPWE), and the channelized Hotelling observer (CHO). Human 2AFC experiments involving four physicist observers were also performed to provide reference to the model observer results. The contrast thresholds required for 92% correct decision rate in 2AFC tests were evaluated for each observer. While all five model observers show good correlations with human observers, the CHO generated the best quantitative agreement with human observer results. Compared with the time-consuming human observer method, the model observer method is of much higher efficiency for the evaluation and optimization of DPC-CT.

Current advances in CT dose reduction and image quality improvement mechanisms rely on moving towards a more patient / image specific approach. For example, statistical reconstruction algorithms tailor reconstruction weights to patient attenuation values and CT protocols make use of different kVp and mAs settings for different body regions and sizes. In this paper, for the first time to our knowledge, experimental results are presented in which a dynamic bowtie filter was used to tailor the imaging dose during a CT acquisition. The device used to implement a dynamic bowtie is referred to as a digitial beam attenuator (DBA). A non-DBA (non-modulated) CT scan was also performed for comparison. At half of the imaging dose, the noise uniformity of the DBA CT images was 37% better than the non-DBA scan. The use of a dynamic bowtie filter may also prove useful in photon counting CT (PCCT) where high fluence rates and large differences in fluence across projections and from view to view make implementing PCCT difficult. Results are presented in this paper showing dynamic range requirements of 7.9 and 13.8 for DBA and non-DBA scans respectively. The results also show that when using the DBA, the dose delivered can be reduced by 1.9 times for the small phantom used in this study. The differences in dynamic range and dose are somewhat small compared to what would be seen clinically due to the small size of the phantom used in the study. Using a more clinically relevant phantom, dynamic range differences of 22 times and dose reductions on the order of 4 times can be observed in which the effects of the DBA will be more dramatic.

Purpose: Dual-energy cone-beam CT (DE-CBCT) is an emerging technology with potential application in diagnostic imaging and image-guided interventions. This paper reports DE-CBCT feasibility and investigates decomposition algorithms for maximizing low-dose performance for reconstruction-based DE decomposition. A framework of binary decision theory is used to examine the accuracy of DE decompositions obtained from analytical reconstructions of differentially filtered low-energy (LE) and high-energy (HE) data and from penalized likelihood (PL) reconstructions with differential regularization using quadratic and total variation penalties. Methods: Accurate DE-CBCT decomposition benefits from consideration of all system noise components. Filtered backprojection (FBP) reconstruction-based decomposition was investigated with differential filtering of LE and HE data. Penalized likelihood reconstruction-based decomposition with differential regularization was hypothesized to further improve low-dose performance, especially when coupled with regularization through a total variation edge preserving penalty that encourages piecewise smooth images. Performance of decomposition was assessed in terms of a binary hypothesis framework of sensitivity, specificity, and accuracy. Studies involved experiments on a DE-CBCT testbench, phantoms of variable material type and concentration, and cadavers (knee arthrography). Results: Studies support the overall feasibility of accurate, low-dose DE-CBCT at concentration down to 5 mg/ml (iodine), dose ~3-6 mGy, and accuracy of material classification ~90%. Reconstruction-based decomposition with quadratic PL performed comparably to FBP. PL with a total variation penalty provided edge preservation and piecewise smooth images that aided DE classification and achieved improved performance over FBP and quadratic PL, reaching accuracy of ~0.98 for 2 mg/mL iodine at 3.2 mGy, compared to approx. 0.9 for FBP and quadratic PL. Conclusions: Accurate material decomposition with DE-CBCT is feasible at low dose and benefits from a rigorous assessment of noise mechanisms among various reconstruction-based techniques. The work points to the potential for non-linear iterative reconstruction methods for high-quality decomposition at low material concentration and dose.

In the current workflow of ischemic stroke management, it is highly desirable to obtain perfusion information with the C-arm CBCT system in the interventional room. Due to hardware limitations, the data acquisition speed of the current Carm CBCT systems is relatively slow and only 7 time frames are available for a 45 s perfusion study. In this study, a novel temporal recovery method was proposed to recover contrast enhancement curves in C-arm CBCT perfusion studies. The proposed temporal recovery problem is a constrained optimization problem. Two numerical methods were used to solve the proposed problem. The feasibility of proposed temporal recovery method was validated with numerical experiments. Both solvers can achieve a satisfactory solution for the temporal recovery problem, while the result of the Bregman algorithm is more accurate than that from the CG. In vivo animal studies were used to demonstrated the improvement of the proposed method in C-arm CBCT perfusion. A stoked canine model was scanned with both C-arm CBCT and diagnostic CT. Perfusion defects can be clearly indentified from the cerebral blood flow (CBF) map of diagnostic CT perfusion. Without the temporal recovery technique, these defects can hardly be identified from the CBCT CBF map. After applying the proposed temporal recovery method, the CBCT CBF map well correlates with the CBF map from diagnostic CT.

We propose a motion compensation approach based on algebraic reconstruction in case of coarse motion grid. The method is tested with Shepp-Logan phantom.

In X-ray imaging, a reduction of the field of view (FOV) is proportional to a reduction in radiation dose. The resulting truncation, however, is incompatible with conventional tomographic reconstruction algorithms. This problem has been studied extensively. Very recently, a novel method for region of interest (ROI) reconstruction from truncated projections with neither the use of prior knowledge nor explicit extrapolation has been published, named Approximated Truncation Robust Algorithm for Computed Tomography (ATRACT). It is based on a decomposition of the standard ramp filter into a 2D Laplace filtering (local operation) and a 2D Radon-based filtering step (non-local operation). The 2D Radon-based filtering that involves many interpolations complicates the filtering procedure in ATRACT, which essentially limits its practicality. In this paper, an optimization for this shortcoming is presented. That is to apply ATRACT in one dimension, which implies that we decompose the standard ramp filter into the 1D Laplace filter and a 1D convolutionbased filter. The convolution kernel was determined numerically by computing the 1D impulse response of the standard ramp filtering coupled with the second order anti-derivative operation. The proposed algorithm was evaluated by using a reconstruction benchmark test, a real phantom and a clinical data set in terms of spatial resolution, computational efficiency as well as robustness of correction quality. The evaluation outcomes were encouraging. The proposed algorithm showed improvement in computational performance with respect to the 2D ATRACT algorithm and furthermore maintained reconstructions of high accuracy in presence of data truncation.

Dedicated breast CT (bCT) technology may be useful for patients with high risk of developing breast cancer. Previous studies have shown that bCT outperforms mammography in the visualization of mass lesions, however mammography is superior in identifying microcalcifications. The Breast Tomography Project at UC Davis has led to development of three dedicated breast CT scanners that produce high resolution, fully tomographic images, overcoming tissue superposition effects found in mammography while maintaining an equivalent radiation dose. Over 600 patients have been imaged in an ongoing clinical trial. The first patient scan was performed on the latest bCT scanner developed at UC Davis, called Cambria, on April 12, 2012. The main differences between Cambria and the previous scanners are in using a pulsed xray source (generator and tube) instead of continuous x-ray sources, and also in using the non-binning mode of the flatpanel fluoroscopic detector. The spatial resolution characteristics of the new scanner were investigated and the results show significant improvement in the overall MTF properties. Based on these results, it was concluded that using the pulsed x-ray tube, we were able to restore the MTF degradation caused by motion blurring effect that exists in previous generations of bCT. Moreover, MTF analysis shows that using the detector in the native acquisition mode (1 x 1) results in superior spatial resolution which will likely bring considerable improvement to the delineation of microcalcifications.

The quantification of lung nodule volume from CT images provides valuable information for cancer diagnosis and staging. However, the usefulness of quantification depends on its precision. Direct assessment of the volume quantification precision involves multiple steps and can become intractable for a multiplicity of protocols. To assess quantification precision efficiently, we developed a prediction model, named the estimability index (e’). e’ provides a prediction of precision based on the characteristics of image noise and resolution, the nodule being quantified, and the segmentation software. It was further calibrated against empirical precision for 45 protocols of various reconstruction algorithms, slice thickness, and dose level. Results showed a strong correlation established between e’ and the empirical precision across all 45 protocols, demonstrating e’ as an effective surrogate of quantification precision. This study provides a useful framework for the optimization of CT protocols in terms of quantification precision. It also enables fast assessment of protocol compliance in terms of precision for biomarker quantification.

C-arm cone-beam CT is an emerging tool for intraoperative imaging, but currently exhibits modest soft-tissue imaging capability. This work adapts a spectrum of statistical iterative reconstruction approaches to C-arm CBCT and investigates performance in imaging of low-contrast tasks pertinent to soft-tissue surgical guidance. Experiments involved a mobile C-arm and phantoms and cadavers presenting soft-tissue structures imaged using 3D FBP and penalized likelihood reconstruction. Statistical reconstruction - especially non-quadratic PL - boosted soft-tissue image quality through reduction of noise and artifacts, therefore presenting promise for interventional imaging. Further investigation of task-specific performance may overcome conventional tradeoffs in noise, resolution, and dose.

Purpose: Nonstationarity of CT noise presents a major challenge to the assessment of image quality. This work presents models for imaging performance in both filtered backprojection (FBP) and penalized likelihood (PL) reconstruction that describe not only the dependence on the imaging chain but also the dependence on the object as well as the nonstationary characteristics of the signal and noise. The work furthermore demonstrates the ability to impart control over the imaging process by adjusting reconstruction parameters to exploit nonstationarity in a manner advantageous to a particular imaging task. Methods: A cascaded systems analysis model was used to model the local noise-power spectrum (NPS) and modulation transfer function (MTF) for FBP reconstruction, with locality achieved by separate calculation of fluence and system gain for each view as a function of detector location. The covariance and impulse response function for PL reconstruction (quadratic penalty) were computed using the implicit function theorem and Taylor expansion. Detectability index was calculated under the assumption of local stationarity to show the variation in task-dependent image quality throughout the image for simple and complex, heterogeneous objects. Control of noise magnitude and correlation was achieved by applying a spatially varying roughness penalty in PL reconstruction in a manner that improved overall detectability. Results: The models provide a foundation for task-based imaging performance assessment in FBP and PL image reconstruction. For both FBP and PL, noise is anisotropic and varies in a manner dependent on the path length of each view traversing the object. The anisotropy in turn affects task performance, where detectability is enhanced or diminished depending on the frequency content of the task relative to that of the NPS. Spatial variation of the roughness penalty can be exploited to control noise magnitude and correlation (and hence detectability). Conclusions: Nonstationarity of image noise is a significant effect that can be modeled in both FBP and PL image reconstruction. Prevalent spatial-frequency-dependent metrics of spatial resolution and noise can be analyzed under assumptions of local stationarity, providing a means to analyze imaging performance as a function of location throughout the image. Knowledgeable selection of a spatially-varying roughness penalty in PL can potentially improve local noise and spatial resolution in a manner tuned to a particular imaging task. Keywords: cascaded systems analysis, nonstationarity, filtered backprojection, penalized-likelihood reconstruction, noise-power spectrum, covariance matrix, imaging task, detectability index

Assessment of the resolution properties of nonlinear imaging systems is a useful but challenging task. While the modulation transfer function (MTF) fully describes contrast resolution as a function of spatial frequency for linear systems, an equivalent metric does not exist for systems with significant nonlinearity. Therefore, this preliminary investigation attempts to classify and quantify the amount of scaling and distortion imposed on a given image signal as the result of a nonlinear process (nonlinear image processing algorithm). As a proof-of-concept, a median filter is assessed in terms of its principle frequency response (PFR) and distortion response (DR) functions. These metrics are derived in frequency space using a sinusoidal basis function, and it is shown that, for a narrow-band sinusoidal input signal, the scaling and distortion properties of the nonlinear filter are described exactly by PFR and DR, respectively. The use of matched sinusoidal basis and input functions accurately reveals the frequency response to long linear structures of different scale. However, when more complex (multi-band) input signals are considered, PFR and DR fail to adequately characterize the frequency response due to nonlinear interaction effects between different frequency components during processing. Overall, the results reveal the context-dependent nature of nonlinear image processing algorithm performance, and they emphasize the importance of the basis function choice in algorithm assessment. In the future, more complex forms of nonlinear systems analysis may be necessary to fully characterize the frequency response properties of nonlinear algorithms in a context-dependent manner.

X-ray scatter degrades image contrast, uniformity and CT number accuracy in cone-beam computed tomography (CBCT). Correction methods based on the scatter kernel superposition (SKS) technique are efficient and suitable for many clinical applications but still produce residual errors due to limitations in the scatter kernel models. To reduce these errors, we propose to generate a first-pass reconstruction using a set of default SKS parameters followed by limited Monte Carlo simulations that are then used to perturb and refine key kernel parameters in order to obtain an improved second-pass correction. To test the approach, we used the fast adaptive scatter kernel model (fASKS) employing asymmetric kernels for the first-pass scatter correction and then used GEANT4 to simulate scatter-to-primary ratios in selected projections allowing for refined scatter estimates. The results show that a minimal number of projections require simulation in order to adequately perturb scatter kernel parameters for all projections. Compared to the default asymmetric kernels, the refined kernels reduced CT number errors from 24 HU to 15 HU in a large pelvis phantom resulting in a more uniform and accurate image.

Variational methods are useful for solving ill-posed inverse imaging problems by minimizing a cost function with a data fidelity term and a regularization term. For statistical X-ray computed tomography (CT) image reconstruction, penalized weighted least-squares (PWLS) criteria with edge-preserving regularization can improve quality of the reconstructed image compared to traditional filtered back-projection (FBP) reconstruction. Nevertheless, the huge dynamic range of the statistical weights used in PWLS image reconstruction leads to a highly shift-variant local impulse response, making effective preconditioning difficult. To overcome this problem, iterative algorithms based on variable splitting were proposed recently. However, existing splitting-based iterative algorithms do not consider the (unknown) gain fluctuations that can occur between views. This paper proposes a new variational formulation for splitting-based iterative algorithms where the unknown gain parameter vector and the image are estimated jointly with just simple changes to the original algorithms. Simulations show that the proposed algorithm greatly reduces the shading artifacts caused by gain fluctuations yet with almost unchanged computational complexity per iteration.

The increase in the use of CT scanning in the clinical setting is raising concerns from the medical community. In order to reduce the dose of ionizing radiation imparted to patients during CT scans, statistical image recon­ struction was proposed. This family of algorithm aims at improving image noise characteristics by modeling the stochastic x-ray detection process in the reconstruction algorithm. It was shown however that statistical recon­ struction may lead to an anisotropic spatial resolution. In this abstract, we study this tradeoff in the context of a statistical formulation of the dose reduction using prior image constrained compressed sensing framework (DR-PICCS). Two numerically-simulated phantoms and a dataset acquired in vivo were used for this evaluation. It is demonstrated that the inclusion of a statistical model in DR-PICCS may whiten the NPS and uniformize the noise spatial distribution in the image. However, the images may suffer from an anisotropic spatial resolution while the images reconstructed using DR-PICCS without statistical model have more isotropic spatial resolution. Due to the flexibility offered in PICCS, a specially-designed prior image processing method has been used in statistical DR-PICCS to palliate for the anisotropy in spatial resolution.

Nonlinear partial volume (NLPV) effects can be significant for objects with large attenuation differences and fine detail structures near the spatial resolution limits of a tomographic system. This is particularly true for small metal devices like cochlear implants. While traditional model-based approaches might alleviate these artifacts through very fine sampling of the image volume and subsampling of rays to each detector element, such solutions can be extremely burdensome in terms of memory and computational requirements. The work presented in this paper leverages the model-based approach called “known-component reconstruction” (KCR) where prior knowledge of a surgical device is integrated into the estimation. In KCR, the parameterization of the object separates the volume into an unknown background anatomy and a known component with unknown registration. Thus, one can model projections of an implant at very high spatial resolution while limiting the spatial resolution of the anatomy - in effect, modeling NLPV effects where they are most significant. We present modifications of the KCR approach that can be used to largely eliminate NLPV artifacts, and demonstrate the efficacy of the modified technique (with improved image quality and accurate implant position estimates) for the cochlear implant imaging scenario.

Advances have been made in recent years in computed tomography (CT) as a result of the development and implementation of new iterative reconstruction methods. Prior Image Constrained Compressed Sensing (PICCS) is one such iterative reconstruction method which iteratively minimizes an objective function to approach a target image. To date, published studies have employed the L₁ norm in the minimization of the objective function. In this study, we investigate the use of L_p norms with p > 1 and investigate how image quality depends on the selection of the L_p norm used in the minimization of the objective function.

The forward projection operator is a key component of every iterative reconstruction method in X-ray computed tomography (CT). Besides the choices being made in the definition of the objective function and associated constraints, the forward projection model affects both bias and noise properties of the reconstruction. In this work, we compare three important forward projection models that rely on linear interpolation: the Joseph method, the distance-driven method, and the image representation using B-splines of order n = 1. The comparison focuses on bias and noise in the image as a function of the resolution. X-ray CT data that are simulated in fan-beam geometry with two different magnification factors are used.

Correlated-polarity noise reduction (CPNR) is a novel noise reduction technique that uses a statistical approach to reduce noise while maintaining excellent resolution and a “normal” noise appearance. It is applicable to any type of medical imaging, and we introduced it at SPIE 2011 for reducing dose three-fold in radiography while maintaining excellent image quality. In this current work, we demonstrate for the first time its use in reducing the noise in CT images as a means of reducing the dose in CT. Simulated chest CT images were generated using the XCAT phantom and Poisson noise was added to simulate a conventional full-dose CT image and a half-dose CT image. CPNR was applied to the half-dose images in projection image space, and then the images were reconstructed using filtered backprojection with a Feldkamp methodology. The resulting CPNR processed half-dose images showed essentially equivalent relative standard deviation in the central heart region to the full-dose images, and about 0.7 times that in half-dose images that were not processed with CPNR. This noise reduction was consistent with a two-fold reduction in dose that is possible with CPNR in CT. The CPNR images demonstrated virtually identical sharpness of vessels and no apparent artifacts. We conclude that CPNR shows strong promise as a new noise reduction method for dose reduction in CT. CPNR could also be used in combination with model-based iterative reconstruction techniques for yet further dose reduction.

Scatter contamination in cone-beam computed tomography (CBCT) degrades the image quality by introducing shading artifacts. In our previous study, a moving-blocker-based approach was proposed to simultaneously estimate scatter and reconstruct the complete volume within field of view (FOV) from a single CBCT scan. Promising results were obtained from simulation studies. In this work, we implemented the moving blocker system on a LINAC on-board kV CBCT imaging system. A physical attenuator (i.e., "blocker") consisting equal spaced lead strips was mounted on a linear actuator. A step motor connected to the actuator drove the blocker to move back and forth along gantry rotation axis during CBCT acquisition. Scatter signal was estimated from the blocked region of imaging panel, and interpolated into the un-blocked region. A sparseness prior based statistical iterative reconstruction algorithm was used to reconstruct CBCT images from un-blocked projections after the scatter signal was subtracted. Experimental studies were performed on both a Catphan phantom and an anthropomorphic pelvis phantom to evaluate performance of the moving blocker system. The scatter-induced shading artifacts were substantially reduced in the images acquired with the moving blocker system. CT number error reduced in selected regions of interest of the Catphan phantom from 318 to 17. It also decreased in those of the pelvis phantom from 239 to 10. We demonstrated for the first time that the moving blocker system could successfully estimate the scatter signal in projection data, reduce the imaging dose and obtain complete volumetric information within the FOV using a single scan.

Dynamic attenuators are beam shaping filters that can customize the x-ray illumination field to the clinical task and for each view. These dynamic attenuators replace traditional attenuators (or “bowtie filters”) and decrease radiation dose, dynamic range, and scatter when compared to their static counterparts. We propose a one-dimensional dynamic attenuator that comprises multiple wedges with axially-dependent triangular cross-sections, and which are translated in the axial direction. These wedges together produce a time-varying, piecewise-linear attenuation function. We investigate different control methods for this attenuator and estimate the ability of the dynamic attenuator to reduce dose while maintaining the peak variance of the scan. With knowledge of the patient anatomy, the dynamic attenuator can be controlled by solving a convex optimization problem. This knowledge could be determined from a low dose pre-scan. Absent this information, various heuristics can be used. We simulate the dynamic attenuator on datasets of the thorax, abdomen, and a targeted scan of an abdominal aortic aneurysm. The dose and scatter-to-primary ratio (SPR) are estimated using Monte Carlo simulations, and the noise is calculated analytically. Compared to a system using the standard bowtie with typical mA modulation, dose reductions of 50% are observed. Compared to an optimized, patientspecific mA modulation, the typical dose reduction is 30%. If the dynamic attenuator is controlled with a heuristic, typical dose reductions are also 30%. The gains are larger in the targeted scan. The SPR is also reduced by 20% in the abdomen. We conclude that the dynamic attenuator has significant potential to reduce dose without increasing the peak variance of the scan.

It is highly desirable to obtain perfusion information with the C-arm CBCT system in the interventional room. However, due to hardware limitations, it is still elusive to achieve cone-beam CT perfusion measurements. In this study, we performed a systematic study to investigate what the main limiting factors are that need to be addressed for future C-arm cone beam CT perfusion imaging. To do so, we performed systematic numerical simulation studies using a diagnostic CT perfusion data set. Specifically, a forward projection was performed to simulate cone-beam CT perfusion experiment with C-arm CBCT geometry and temporal behavior. Different x-ray delays after contrast injection have been simulated with this method. The view angle undersampling artifacts, shading artifacts from dynamic objects, and the importance of arterial input function (AIF) for perfusion study were investigated in this study with different x-ray delay times. From the simulation results, it was found that the view angle undersampling artifacts do not have much impact on perfusion maps. The shading artifacts from dynamic object were shown to have a negligible effect on the NRMSE in perfusion maps. The accuracy of AIF is an important but not a dominating factor for perfusion studies. C-arm CBCT cannot accurately recover the slowly changing contrast in brain tissues due to the low temporal resolution. Therefore, to enable cone beam C-arm CT perfusion measurement, it is critical to improve the temporal behavior of CBCT by either employing new hardware upgrades or introducing new software methods.

Misalignment-Correction in C-arm-based flat-detector CT (FD-CT) is a frequently discussed problem. To avoid artifacts caused by geometrical instabilities, numerous methods for misalignment correction were investigated. Most of them make use of a foregoing calibration routine, based on scanning a specific phantom. The aim of this study is to develop and evaluate an online image-content-based calibration technique without using any kind of marker or calibration phantom. The introduced method is based on a gradient descent method, minimizing an entropy criterion which is used to optimize the underlying geometry parameters of the acquisition system. It is formed as multistep approach, including a global, local and projection wise optimization. This enables the elimination of general system misalignments, as well as a reduction of streak artifacts and the adjustment of patient motion artifacts. Phantom and patient measurements with the C-arm FD-CT system Artis Zeego (Siemens AG, Healthcare Sector, Forchheim, Germany) were used to validate the algorithm for realistic applications. It reduced most of the actual misalignment and increased image quality drastically. Phantom-studies, starting from the standard system geometry without a foregoing calibration showed very good results. Online-calibration is possible with our approach and therefore, the limitation to predefined scan-protocols is obsolete. The evaluation of patient datasets brought out the same conclusions and provides the implication of simultaneous patient motion compensation.

Based on a phantom study with a realistic coronary vessel phantom, we investigated if motion compensated cardiac CT reconstruction can improve best phase image quality with respect to motion artifacts and patency of coronary vessel lumen. Basically, tracking based methods (with and without improvement of temporal resolution) deriving the motion fields by a registration-like procedure are compared to optimization based methods optimizing objective functions while minimizing artifact levels (e.g. Motion Artifact Metric Optimization (MAM) Reconstruction). Using the MAM technique, the motion field is iteratively calculated with a steepest descent update equation minimizing a motion artifact metric. We evaluated patency of the vessel lumen, the normalized cross correlation (NCC) of the respective reconstruction data with the ground truth data and a best phase improvement index correlating the motion compensated reconstruction data to the non-compensated FDK-based reconstruction data. It will be shown that the MAM technique is superior to the tracking methods. The latter proved to be more or less susceptible to template matching and, or erroneous template size. The value of MAM is also demonstrated evaluating clinical data. In particular it is beneficial for patients with high heart rates as well as for dose optimized scan protocols because it does not need over-radiation.

Two-photon annihilation quanta are emitted in a pure quantum state and when detected in coincidence, the photon pairs possess orthogonal polarizations. We propose that this polarization correlation can be exploited in Positron Emission Tomography (PET), which relies crucially on accurate coincidence detection of photon pairs. In this proof of concept study, we investigate how photon polarization information can be exploited in PET imaging by developing a method to discern true coincidences using the polarization correlation of annihilation pairs. We demonstrate that the unique identification of true photon pairs with their polarization correlation can dramatically enhance overall PET image quality, especially for high emission rates, when conventional, energy- based coincidence detection methods become increasingly unreliable. Our results suggest that polarization-based coincidence detection offers new prospects for in vivo molecular imaging with next-generation PET systems.

Purpose: Some qualitative studies report a preference for blended dual-energy (DE) CT images over single energy (SE) images for liver CT imaging at the same dose. This is counter to theoretical expectations for simple tasks. We hypothesized that perhaps the broad spectrum of DE might be beneficial for a combination of tasks. We compare the CNR of SE and blended DE images for single and composite tasks, in part to see if they explain the preference. Methods: We simulated pre- and post-contrast SE abdominal CT imaging at various kVp but at constant average dose. Next, 80kVp and 140kVp scans with different dose allocations, dose matched to the SE images, were simulated. DE images were blended linearly with optimized blending ratios. The CNRs of liver against other soft tissues were used as a composite image quality metric for evaluation and comparison between the SE and DE protocols. In addition, the combination of the CNR of many tissue pairs pre- and post-contrast. Results: The CNR of pre-contrast single kVp imaging mostly increases with increasing tube voltage while 90kVp or lower energy yields higher CNR for post-contrast images, depending on the differential iodine concentration of each tissue. Similar trends are seen in the DE blended CNR curves. Results from the composite multi-CNR metric demonstrate that the SE protocol has better performance. Conclusions: Our study showed that an optimized SE protocol produces higher CNR, even for a range of tasks. This suggests that the reason for the radiologist preference must be something other than a fundamental advantage of DE.

Attenuation and scatter correction in single photon emission computed tomography (SPECT) imaging often requires a computed tomography (CT) scan to compute the attenuation map of the patient. This results in increased radiation dose for the patient, and also has other disadvantages such as increased costs and hardware complexity. Attenuation in SPECT is a direct consequence of Compton scattering, and therefore, if the scattered photon data can give information about the attenuation map, then the CT scan may not be required. In this paper, we investigate the possibility of joint reconstruction of the activity and attenuation map using list- mode (LM) SPECT emission data, including the scattered-photon data. We propose a path-based formalism to process scattered-photon data. Following this, we derive analytic expressions to compute the Cram´er-Rao bound (CRB) of the activity and attenuation map estimates, using which, we can explore the fundamental limit of information-retrieval capacity from LM SPECT emission data. We then suggest a maximum-likelihood (ML) scheme that uses the LM emission data to jointly reconstruct the activity and attenuation map. We also propose an expectation-maximization (EM) algorithm to compute the ML solution.

Recent advances in energy-resolved CT can potentially improve contrast-to-noise ratio (CNR), which could subsequently reduce dose in conventional and dedicated breast CT. Two methods have been proposed for optimal energy weighting: weighting the energy- bin data prior to log normalization (projection- based weighting) and weighting the energy-bin data after log normalization (image-based weighting). Previous studies suggested that optimal projection-based and image-based energy weighting provide similar CNR improvements for energy­ resolved CT compared to photon-counting or conventional energy-integrating CT. This study experimentally investigated the improvement in CNR of projection-based and image-based weighted images relative to photon­ counting for six different energy-bin combinations using a bench top system with a CZT detector. The results showed CNR values ranged between 0.85 and 1.01 for the projection- based weighted images and between 0.91 and 1.43 for the image- based weighted images, relative to the CNR for the photon-counting image. The range of CNR values demonstrates the effects of energy-bin selection on CNR for a particular energy weighting scheme. The non-ideal spectral response of the CZT detector caused spectral tailing, which appears to generally reduce the CNR for the projection-based weighted images. Image-based weighting increased CNR in five of the six bin combinations despite the non-ideal spectral effects.

Novel methods of reconstructing the tracer distribution in myocardial perfusion images are being considered for lowcount and sparse sampling scenarios. Few examples of low count scenarios are when the amount of radioisotope administered or the acquisition time is lowered, in gated studies where individual gates are reconstructed. Examples of sparse angular sampling scenarios are patient motion correction in traditional SPECT where few angles are acquired at any given pose and in multi-pinhole SPECT where the geometry is sparse and truncated by design. The reconstruction method is based on the assumption that the tracer distribution is sparse in the transform domain, which is enforced by a sparsity-promoting penalty on the transform coefficients. In this work we investigated the curvelet transform as the sparse basis for myocardial perfusion SPECT. The objective is to determine if myocardial perfusion images can be efficiently represented in this transform domain, which can then be exploited in a penalized maximum likelihood (PML) reconstruction scheme for improving defect detection in low-count/ sparse sampling scenarios. The performance of this algorithm is compared to standard OSEM with 3D Gaussian post-filtering using bias-variance plots and numerical observer studies. The Channelized Non-prewhitening Observer (CNPW) was used for defect detection task in a “signalknown- statistically” LROC study. Preliminary investigations indicate better bias-variance characteristics and superior CNPW performance with the proposed curvelet basis. However, further assessment using more defect locations and human observer evaluation is needed for clinical significance.

This work investigates a dual-energy subtraction technique for cone-beam breast CT combined with an iodinated contrast agent. Simulations were performed to obtain optimally enhanced iodine-equivalent and morphological images. The optimal x-ray beam energies and average glandular dose allocation between the LE and HE images were identified. Cylindrical phantoms were simulated with 10, 14 and 18 cm diameters and composed of 50% fibroglandular breast tissue equivalent material. They contained spherical lesion inserts composed of 0, 25, 75 and 100% fibroglandular equivalent tissues, homogeneous mixtures of 50% fibroglandular equivalent tissue and 0.5, 1.0, 2.5 and 5.0 mg/cm³ iodine, as well as pure calcium hydroxyapatite, emulating calcifications. An acquisition technique with 600 projection images is proposed. Only primary x-ray photons were simulated and a perfect energy-integrating detector was considered. LE and HE beams ranging from 20 keV to 80 keV were investigated. The LE and HE projections were reconstructed using a filtered backprojection algorithm. The LE volume provided the morphological image while the iodine-equivalent volume was obtained by recombining the LE and HE volumes. Contrast-to-noise ratio (CNR) between the spherical inserts and background breast tissue normalized to the square root of the total AGD (CNRD) was used as figure-of-merit for lesion detectability. Based on maximizing CNRD, a 30keV/34keV LE/HE pair and a ~50/50% LE/HE AGD allocation were found to provide the best possible performance for iodine and morphological imaging for an average size breast.

Knowledge of x-ray attenuation is essential for developing and evaluating x-ray imaging technologies. For instance, techniques to better characterize cysts at mammography screening would be highly desirable to reduce recalls, but the development is hampered by the lack of attenuation data for cysts. We have developed a method to measure xray attenuation of tissue samples using a prototype photon-counting spectral mammography unit. Spectral (energyresolved) images were acquired and the image signal was mapped to two known reference materials, which were used to derive the x-ray attenuation as a function of energy. We have measured the attenuation of 25 samples of breast cyst fluid. Spectral measurements of water samples showed consistent results compared to published attenuation values.

This work investigated the substitution of CDMAM contrast detail (c-d) analysis with detectability (d’) from a nonprewhitening eye filter model observer (NPWE) for routine quality control (QC). Routinely acquired QC data for 53 systems were analyzed: 13 computed radiography (CR) and 40 integrated detector (DR) systems. For a given system, threshold gold thickness from the c-d analysis (T) was calculated from 16 images and compared against d’ calculated for 0.1 and 0.25 mm diameter discs. The d’ data were calculated from the routine 50 mm PMMA AEC image and the measured pre-sampling detector modulation transfer function (MTF). Threshold gold thickness T and d’ were plotted as function of MGD and compared. The Fuji CR and the Agfa CR systems had the highest T values compared to the other systems. The Hologic systems were found to have a low value of T, compared to the other systems, for both disc diameters. The NPWE results reflected the performance seen for T data for the majority of the systems with the exception of the Fuji CR and Konica CR systems. The Hologic systems gave unexpectedly low d’ results or unexpectedly low T values. The correspondence between the two quality indices was examined with the Pearson correlation statistical test. This test was not applicable to the GE Essential systems because all systems are grouped together at the same working point so the result of r is about 0. For all other groups of systems the test gave good results (larger than -0.65).

Computerized algorithms are increasingly being developed for quantifying breast MRI features for facilitating lesion detection and breast tissue segmentation in various clinical applications. One of the current impediments is the intensity non-standardness of the breast tissue in the acquired MR images across different cases, scanners, and/or patients. This degrades the performance of quantitative image processing. In this work, we investigate the usefulness of post-hoc intensity standardization of breast MR images by using a landmark-based nonlinear intensity mapping algorithm. The standardization algorithm is applied after correction of the images for background bias field non-uniformity. We then quantitatively compare the percentage coefficient of variation (%CV) of image intensity in the fibroglandular (e.g., dense) tissue region before and after standardization to evaluate the standardization procedure. In our experiments, we use 9 representative 3D bilateral breast MRI scans/cases constituting 18 breasts (a total of 504 tomographic breast MRI slices), in which we observe a significant decrease of the %CV in the standardized images, indicating that standardization significantly reduces the intensity variation for the fibroglandular tissue across these cases. Furthermore, we demonstrate for two segmentation methods that the standardization process leads to improved segmentation of the fibroglandular tissue. Our work suggests that intensity standardization following bias field correction may serve as an effective preprocessing step to support improved quantitative breast MR image processing and analysis, particularly for breast density quantification.

Dual-energy digital mammography (DEDM) can generate tissue-subtracted calcification image for improving the detectability of breast calcifications. However, the masses, if present, are missing in the tissue-subtracted calcification image. This paper proposes an algorithm to generate conventional mammographic image by DEDM images based on a multi-scale decomposition and reconstruction architecture with Gaussian filters. Firstly, calibration coefficients are measured at different kVp to correct the original LE and HE. Secondly, the LE and HE images are decomposed into multi-scale components. Thirdly, the components at different scale of the two images are weighted based on a similarity measure to generate new components. Finally, the conventional mammographic image is reconstructed by these new components using noise suppression technique. The proposed method was validated by different breast phantoms on two commercially available full-field digital mammography systems. Results show that the method is effective and the reconstructed image has similar grayscale, contrast and noise level to the corresponding conventional mammogram. Therefore, both the calcification image and conventional mammogram-like image can be generated; the patient will not need more exposure to get the conventional mammogram in DEDM.

Software breast phantoms have been developed for pre-clinical validation of breast imaging systems. Realism is of great importance for the acceptance and the range of applications of breast phantoms. In this paper we have assessed the phantom realism based upon the analysis of mammographic texture properties. Texture analysis is of interest since it reflects the spatial tissue distribution, which is known to correlate with breast cancer risk. We compared texture properties of synthetic mammograms generated using software breast phantoms with clinical data. A total of 133 phantom images were synthesized using software phantoms developed at the University of Pennsylvania. The phantoms were designed using two different anatomy simulation methods: an octree-based recursive partitioning method and a region growing method. The synthetic images were generated assuming a clinically used acquisition geometry and mono-energetic x-ray beam with no scatter. The clinical data included 60 anonymized mammograms selected retrospectively from screening cases at the University of Pennsylvania. The same postprocessing was applied to clinical and phantom images. The texture analysis was performed using fully automated software which extracts a battery of features from analyzed images. The histograms of texture properties extracted from phantom images were compared with those from clinical mammograms, separately for the two anatomy simulation methods. The histogram agreement was quantified using symmetrized Kulback-Leibler divergence. We observed good agreement for most of the analyzed 25 features. In more than a half of the features, the octree-based simulation method yielded better agreement with clinical data as compared with the region growing method.

Purpose: This study aimed at assessing patient dose with standard and low-dose MDCT fluoroscopy protocols for lung biopsy. Materials and Methods: The low-dose protocol used lower tube potential (80 kV) respect to the standard protocol (120 kV); all other scanning parameters were left unchanged. Data from sixty-nine (69) CT fluoroscopy (CTF) lung interventions were prospectively collected and included in the study. Nineteen (19) procedures where performed using the standard protocol (120 kV), while the remaining 50 where performed with the low-dose protocol ( 80 kV). Effective patient dose was calculated using the dose-length product information, while peak entrance skin dose was measured with EBT2 gafchromic films. Lesion size, total fluoroscopy time, success rate and complication rate were also recorded. The Mann-Whitney U test was used to assess statistical significant difference in terms of lesion size and fluoroscopy time, between the two study groups. Fisher’s test was used to assess significant difference in terms of success and conclusiveness. Results: The median effective patient dose was 5.4 mSv (minimum 2.4 mSv, maximum 18.8 mSv; 19 procedures) for the standard protocol and 1.1 mSv (minimum 0.4 mSv, maximum 4.5 mSv; 50 procedures) for the low-dose protocol (p<0.01). The median peak entrance skin dose was 268 mGy (95-899 mGy) and 141 mGy (38-410 mGy) for the standard and low-dose protocol respectively (p<0.01). There was no significant difference (p=0.95) in mean lesion size between the two groups: standard protocol 2.7 cm (min 0.9 cm, max 10.7 cm); lowdose protocol 2.6 cm (min 1.0 cm, max 7.9 cm). Average fluoroscopy time was 1.4 min (range 0.6-5.0 min) and 1.3 min (range 0.4-4.5 min), respectively for the standard and low-dose protocol (p-value=0.36). Biopsy performed using the low-dose protocol was technically successful in 98% of the cases and complication rate was 18%, compared to 100% and 10% for the standard protocol. No statistical significant difference was found between the two groups ( p< 0.05). Conclusions: High patient entrance skin dose (up to 899 mGy) and high effective patient dose (up to 18.8 mSv) can occur for standard CTF lung biopsy protocol. Simple means, like lowering the kV, allow reducing patient dose significantly, with skin doses now far below the 2 Gy level of deterministic effects. Occupational doses, occasionally of concern in high work load regimes, are expected to follow the same trend.

Dual-energy CT has the potential to overcome many of the limitations of routine single-energy CT scanning, such a,.., the potential to provide quantitative imaging via electron density, effective atomic munber, and virtual monochromatic imaging and the potential to completely eliminate beam-hardening artifacts via projection space decomposition. While the potential clinical benefit is strong, a possible barrier to more frequent clinical use of dual-energy CT scanning is radiation dose for high quality images. While image quality in dual-energy CT depends on a munber of factors, including dose partitioning, the choice of kV pair, and the amount of pre­ filtration used, a munber of strategies have been employed to improve image quality in dual-energy CT. Four main methods are: (1) increa,..,e the radiation dose, (2) increase the slice thickness, (3) perform voxel averaging, or (4) use noise reduction algorithms. While these methods offer options for improving image quality, ideally, it is desirable not to have to increase radiation dose or sacrifice spatial resolution (in the x-y plane or in the z-direction). Therefore, it is the purpose of this work to investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT to reduce radiation dose without sacrificing image quality. In particular, we investigate the use of PICCS in dual-energy CT to generate material density images at half the radiation dose of a commonly used gemstone spectral imaging (GSI) protocol. lVIaterial density images are generated using half the radiation dose, and virtual monochromatic images are generated as a linear combination of half-dose material density images. In this abstract, qualitative and quantitative evaluation are provided to assess the performance of PICCS relative to FBP images at the full dose level and at the half dose level.

Mammographic breast density is a strong risk factor for breast cancer. Studies on imaging dose in mammography have primarily focused on imaging quality and diagnostic accuracy, while little work has been done on understanding its effect on the estimation of breast density. Studies on the effect of dose on mammographic density estimation can be useful in dose reduction for the purpose of density estimation and monitoring. In this study, we investigate the dependence of percent area (PD%) and volumetric (VD%) breast density estimation on imaging dose using an anthropomorphic breast phantom (Rachel, Gammex). A set of digital mammograms were obtained with a GE Senographe 2000D FFDM system, using 220 unique combinations of different imaging physics, namely target/filter, kVp and mAs. Specifically, 8 different mAs settings were defined as corresponding to 10%, 20%, 40%, 70%, 100%, 150%, 200% and 300% of 1.8 mGy reference average glandular dose (AGD) for standard phototimed exposure. Breast density was estimated using fully-automated FDA-cleared software (Quantra v.2.0, Hologic Inc.). The obtained estimates were analyzed to study the effect of the imaging dose, using ANOVA and linear regression. Results show that there is a statistically significant dependence of density estimation on x-ray imaging dose (p-value=0.014 and <0.001 for PD% and VD%, respectively), while the actual variation of the estimation across the different levels of dose is relatively low (standard deviation of 2.87% and 0.66% for PD% and VD% respectively), the differences could be significant when breast density measures are used for risk estimation.

Radiation monitoring systems able to accurately track the radiation dose received by the patient and the medical staff during interventional fluoroscopy can be used to minimize the likelihood and severity of radiation-induced skin injuries and estimate the accumulated organ doses. We describe a method to monitor doses in real time using automatic sensors in the imaging room and a CPU-accelerated computer simulator. The Monte Carlo simulation code MC-GPU is used to estimate patient and staff doses due to primary and scattered radiation, along with the associated statistical uncertainties. The geometrical configuration of the irradiation is automatically determined and updated using data from a depth camera that tracks the location and posture of each person in the imaging room. A virtual x-ray source graphical interface is used to manually trigger the simulations. The implemented computational framework separates the simulation of the x-ray transport through the patient and the operator bodies into two coupled, sequential simulations. The initial simulation uses the patient anatomy and a c-arm source model with a collimated cone beam emitted from a point focal spot. During this simulation a large phase space file with the energy, position and direction of x rays scattered in the direction of the operator is created. The phase space file is then used as the input radiation source for the following simulation with the operator anatomy model. Particle recycling is employed as a variance reduction technique to maximize the information obtained from the limited number of particles scattered towards the operator. For a typical image acquisition, a patient skin dose map can be displayed at the operator's monitor within 10 seconds with a peak skin dose error below 1%. This work demonstrates that a dose monitoring system based on accurate Monte Carlo simulations can be used to estimate in real-time the average and peak organ doses for both the patient and the staff in interventional fluoroscopy, and provide timely information regarding possible overdoses while the imaging procedure is being performed.

The purpose of this study was to develop and validate a projection-based dose metric that enables computationally efficient dose estimation. The two physical quantities determining dose, absorbed energy and mass, were estimated in projection space. The absorbed energy was estimated using the difference between the imparted energy and detected energy. The mass was estimated using the area under the attenuation profile. A series of phantom simulations were conducted to test the metric’s applicability for multi-material phantoms, different kVp settings, and bowtie filters. Projection-based dose estimates were benchmarked against results from the Monte Carlo (MC) simulation. The projection-based dose metric shows a strong linear correlation with MC dose estimates (R² > 0.96). The prediction errors for projection-based dose metric are below 14%. This study demonstrates a computationally efficient and relatively accurate dose estimation method based on the projection data. It further suggests the possibility to achieve real-time and patient-specific dose optimization when applied prior to a CT scan.

The purpose of this study was to evaluate how different implementations of the tube current modulation (TCM) technology affect organ dose conversion factors in chest CT and how organ dose can be accurately estimated for various modulation schemes. Computational phantom of a normal-weight female patient was used. A method was developed to generate tube current (mA) modulation profiles based on the attenuation of the phantom, taking into account the geometry of the CT system as well as the x-ray energy spectrum and bowtie filtration in a CT scan. The mA for a given projection angle was calculated as a power-law function of the attenuation along this projection. The exponent of this function, termed modulation control strength, was varied from 0 to 1 to emulate the effects of different TCM schemes. Organ dose was estimated for a chest scan for each modulation scheme and was subsequently normalized by volume-weighted CT dose index (CTDI_vol) to obtain conversion factors. The results showed that the conversion factors are second-order polynomial functions of the modulation control strength. The conversion factors established for a fixed-mA scan may be used to estimate organ dose in a TCM scan. For organs on the periphery of the scan coverage, the best accuracy is achieved when using CTDI_vol computed from the average mA of the entire scan. For organs inside the scan coverage, the best accuracy is achieved when using CTDI_vol computed from the volume-averaged mA values of all the axial slices containing the organ.

An analysis of a task based simulation study of coronary artery imaging via computed tomography (CT). Evaluation of standard filtered backprojection (FBP) reconstruction and motion compensated reconstruction of a moving cylindrical vessel that contains a hyper-intense lesion. Multiple conditions are simulated including: varying rest times of the vessel and varying motion orientations. A reference image with no motion was used for all comparisons. The images were segmented and quantitative metrics for accurate segmentation were compared. The motion compensated images have consistent error metrics with respect to the static case for all rest times. The FBP reconstructions were visually inferior for shorter rest times and had significantly inferior metrics. This is the first demonstration of equivalent performance for a given task when the rest times are reduced well below the temporal aperture of the acquisition, using either advanced algorithms or different data acquisition such as multi-source geometries.

In digital radiography imaging, the x-ray images are formed based on a multiplicative model, in which the projected image of an object is multiplied by the antiscatter grid shadow. Hence, the formed image is amplitude- modulated by the grid shadow and the resultant modulated terms appear as the grid artifacts. Since the bandwidths of the modulated terms are as wide as that of the projected image, we should employ relatively wide-bandwidth band-stop filters (BSFs) to reduce the grid artifacts. When we apply such BSFs, the object to be recovered is prone to distortion due to the wide filter bandwidth. In this paper, to reduce the signal bandwidth of the grid shadow images in reduction of the grid artifacts, applying BSFs based on the homomorphic operation is proposed by employing the logarithmic function. By taking the logarithm of the formed image, we can separate the multiplicative grid component from both projected image and the exposure of x-rays. Hence, by employing a relatively narrow and fixed-bandwidth BSFs, we can efficiently alleviate the grid artifacts independently of the strength of the grid artifacts comparing to the conventional linear approaches. For real x-ray images, the superior performance of the proposed approach is compared in this paper.

Volume-of-interest imaging offers the ability to image small volumes at a fraction of the dose of a full scan. Reconstruction methods that do not involve prior knowledge are able to recover almost artifact-free images. Although the images appear correct, they often suffer from the problem that low-frequency information that would be included in a full scan is missing. This can often be observed as a scaling error of the reconstructed object densities. As this error is dependent on the object and the truncation in the respective scan, only algorithms that have the correct information about the extent of the object are able to reconstruct the density values correctly. In this paper, we investigate a method to recover the lost low-frequency information. We assume that the correct scaling can be modeled by a linear transformation of the object densities. In order to determine the correct scaling, we employ an atlas of correctly scaled volumes. From the atlas and the given reconstruction volume, we extract patch-based features that are matched against each other. Doing so, we get correspondences between the atlas images and the reconstruction VOI that allow the estimation of the linear transform. We investigated several scenarios for the method: In closed condition, we assumed that a prior scan of the patient was already available. In the open condition test, we excluded the respective patient’s data from the matching process. The original offset between the full view and the truncated data was 133 HU on average in the six data sets. The average noise in the reconstructions was 140 HU. In the closed condition, we were able to estimate this scaling up to 9 HU and in open condition, we still could estimate the offset up to 23 HU.

Motion tracking for head motion compensation in MRI has been a research topic for several years. However, literature is not giving much attention to the calibration of such setups. We present a method to calibrate the coordinate systems of a stereo-optical camera setup mounted to the MRI head coil. Though using a simple setup and visible instead of infrared light for tracking, it is possible to achieve a sub-millimeter tracking precision. Blue water-filled spheres are positioned throughout the whole MRI imaging volume and detected in images of the tracking cameras as well as MRI scans. In order to register the coordinate systems of both camera system and MRI scanner, a heuristic-enhanced brute-force approach is used to match detected spheres in the different images. Then, a rigid transformation is calculated and applied to the cameras' external parameters to align the coordinate systems. The precision of our setup was evaluated using leave-one-out cross validation both for the camera calibration and the scanner coordinate system registration. We found that the cameras' locations and orientations are correct within 0:03mm and 0:03°, using a number of 45 spheres. Evaluation of the MRI coordinate system registration showed an average reprojection error of 1:1 mm. Influence of a feature point jitter of 0:5 px is 0:03mm for a point close to the cameras and 0:3mm for a point close to the back of the patient's head. Tracked poses are correct within 0:17mm and 0:001.°

In C-arm computed tomography, patient dose reduction by volume-of-interest (VOI) imaging is of increasing interest for many clinical applications. A remaining limitation of VOI imaging is the truncation artifact when reconstructing a 3D volume. It can either be cupping towards the boundaries of the field-of-view (FOV) or an incorrect offset in the Hounsfield values of the reconstructed voxels. In this paper, we present a new method for correction of truncation artifacts in a collimated scan. When axial or lateral collimation are applied, scattered radiation still reaches the detector and is recorded outside of the FOV. If the full area of the detector is read out we can use this scattered signal to estimate the truncated part of the object. We apply three processing steps: detection of the collimator edge, adjustment of the area outside the FOV, and interpolation of the collimator edge. Compared to heuristic truncation correction methods we were able to reconstruct high contrast structures like bones outside of the FOV. Inside the FOV we achieved similar reconstruction results as with water cylinder truncation correction. These preliminary results indicate that scattered radiation outside the FOV can be used to improve image quality and further research in this direction seems beneficial.

This research aims to develop a new feature guided motion estimation method for the left ventricular wall in gated cardiac imaging. The guiding feature is the “footprint” of one of the papillary muscles, which is the attachment of the papillary muscle on the endocardium. Myocardial perfusion (MP) PET images simulated from the 4-D XCAT phantom, which features papillary muscles, realistic cardiac motion with known motion vector field (MVF), were employed in the study. The 4-D MVF of the heart model of the XCAT phantom was used as a reference. For each MP PET image, the 3- D “footprint” surface of one of the papillary muscles was extracted and its centroid was calculated. The motion of the centroid of the “footprint” throughout a cardiac cycle was tracked and analyzed in 4-D. This motion was extrapolated to throughout the entire heart to build a papillary muscle guided initial estimation of the 4-D cardiac MVF. A previous motion estimation algorithm was applied to the simulated gated myocardial PET images to estimate the MVF. Three different initial MVF estimates were used in the estimation, including zero initial (0-initial), the papillary muscle guided initial (P-initial), and the true MVF from phantom (T-initial). Qualitative and quantitative comparison between the estimated MVFs and the true MVF showed the P-initial provided more accurate motion estimation in longitudinal motion than the 0-initial with over 70% improvement and comparable accuracy with that of the T-initial. We concluded that when the footprint can be tracked accurately, this feature guided approach will significantly improve the accuracy and robustness of traditional optical flow based motion estimation method.

Computed tomography (CT) has become a popular tool in radiologic diagnosis due to the ability of obtaining highresolution anatomical images. However, radiation doses to patients are substantial and can increase the risk of cancer incidence. Although lowering the tube current is a direct way to reduce absorbed doses, insufficient photon numbers can cause severe quantum mottle and subsequently degrade the diagnostic value of CT images. In this study, we proposed an algorithm for noise reduction of low-dose computed tomography (LDCT) based on the multiresolution total variation minimization (MRTV) method. The discrete wavelet transform was used to decompose the CT image into high- and lowfrequency wavelet coefficients. The total variation minimization with suitable tuning parameters was then applied to reduce the variance among the wavelet coefficients. The noise-reduced image was reconstructed by the inverse wavelet transform. The results of the Shepp-Logan phantom added with Gaussian white noise showed that the noise was eliminated effectively and the SNR in the three compartments was increased from 2.04, 20.69 and 0.09 to 19.45, 187.77 and 0.27, respectively. In the CT image of the water phantom acquired with 50-mAs tube currents, the MRTV improved the smoothness of the water compartment. The average SNR was increased from 0.14 to 0.98, which is even better than the CT image acquired by 200 mAs. In the clinical head CT image with a tube current of 9.12 mAs, the MRTV successfully removed the severe noise in the parenchyma, and SNR was increased from 0.982 to 3.452 in average. In addition, the details of the septal structure of the sinus cavity were maintained. We conclude that the MRTV approach can effectively reduce the image noise caused by the tube current insufficiency, and thereby could improve the diagnostic value of LDCT images.

The photon spectrum for X-ray capture systems is a function of the emission field angle. Spectrum variability is the most pronounced for cone-beam computed tomography (CBCT) systems with wide field angles operating close to the anode angle limit. Filtration devices also contribute to the change in the photon spectrum with an emission field angle, especially for variable-thickness filters, e.g., bow-tie filters. The change in the photon spectrum is primarily due to the distance traversed through the anode and filtration materials with emission field angles. Although Monte Carlo X-ray simulations can include the materials and geometries for these source assembly elements, the computational requirements are considered prohibitive. As a consequence, most X-ray Monte Carlo simulation implementations ignore emission field angle spectral effects. Our approach uses a probabilistic rejection scheme to model the emission field angle spectral effects within the context of a Monte Carlo simulation tool. A bounding spectrum is constructed that supersedes all possible spectrums, i.e., for all emission field angles. Photons are generated with the bounding spectrum and rejected or accepted based on the probability of transmission through the cascade of anode and filtration materials relative to a pre-calculated maximum probability of transmission. The resultant photon spectrum properly models the intensity and spectral shape of the emitted photons as a function of the emission field angle. The modeling accuracy improvement over the constant spectrum approximation was calculated for a CBCT system for anode voltages ranging from 50 Kvp to 110 Kvp. The maximum improvement in predicted primary and scatter signals was approximately 5% for a system configuration employing a simple filtration and 25% for a CBCT system employing a bow-tie filter with less than a 10% additional computation cost.

In computed tomography (CT), the nonlinear characteristics of beam hardening are due to the polychromaticity of X-rays, which severely degrade the CT image quality and diagnostic accuracy. The correction of beam hardening has been an active area since the early years of CT, and various techniques have been developed. State­ of-the-art works on multi-material beam hardening correction (BHC) are mainly based on segmenting datasets into different materials, and correcting the non-linearity iteratively. Those techniques are limited in correction effectiveness due to inaccurate segmentation. Furthermore, most of them are computationally intensive. In this study, we introduce a fast BHC scheme based on frequency splitting with the fact that beam hardening artifacts mainly contain in the low frequency components and take more iterations to be corrected in comparison with high frequency components. After low-pass filtering and correcting artifacts at down-sampled projections, an artifact reduced high resolution reconstruction will be obtained by incorporating the original edge information from the high frequency components. Evaluations in terms of correction accuracy and computational efficiency are performed using simulated and real CT datasets. In comparison to the BHC algorithm without frequency splitting, the proposed accelerated algorithm yields comparable results in correcting cupping and streak artifacts with tremendously reduced computational effort. We conclude that the presented framework can achieve a significant speedup while still obtaining excellent artifact reduction. This is a significant practical advantage for clinical as well as industrial CT.

Dental imaging often requires to gather information from a curved plane that covers the upper and lower jaw. To acquire these data one may either use a CT or a DVT scan followed by extracting the desired curved plane from the volumetric CT data, or one may decide to work at much lower dose levels and acquire a panoramic radiograph, which is also known as an orthopantomogram, or short as panorama. The panorama is acquired by moving the x-ray source and detector arrangement such that the x-ray cone intersects the curved plane in a preferably perpendicular way. Due to the small size of specialized panorama x-ray detectors, that often run in the so-called time-delayed integration (TDI) mode, the cone is collimated such that it is only a few millimeters wide in the fan direction. In this situation the fan angle is much smaller than the cone angle. Assuming an imaging system based on flat detectors the panoramic imaging corresponds to digital x-ray tomosynthesis taken in a curved plane. Of course, panoramic imaging suffers from significant blurring between adjacent planes, as it is inherent to all tomosynthesis techniques. To reduce this intra plane blurring we propose an approach that uses a form filter to simultaneously acquire the data for a typical orthopantomogram and low-dose data with a significantly increased fan-angle, sufficient to perform a low-dose FDK reconstruction. The bow-tie takes care to reduce dose in that extended region to about 1% compared to the dose in the central region. The total dose remains constant. These data will be combined resulting in an orthopantomogram with improved image quality due to reduced intra plane blurring as one is able to subtract the unwanted background structures arising from off focus objects as for example the cervical vertebrae. We conducted simulations to validate our approach. For that we use a volumetric CT data set of a patient's head from which we generated rawdata. The simulation results show that with our approach panoramic imaging with a flat detector offers the possi­bility to improve image quality without additional costs in patient dose.

Image quality in diagnostic x-ray detectors is limited by statistical properties governing how, and where, x-ray energy is deposited in a detector. This in turn depends on the physics of underlying x-ray interactions, and the development of theoretical models of x-ray interaction physics is therefore a critical step in optimal detector design and assessment. While cascaded-systems analyses are often used to describe image signal and noise in many systems, it has always been assumed there is only a single element (single Z) with which all x rays interact even though most commonly used and promising candidates are compound materials. In addition, coherent and incoherent scattering and their effects on image quality are usually ignored but may be important in some situa- tion such as in low-Z atoms with high x-ray energies. We present a theoretical model of energy deposition within a double-Z x-ray detector material that addresses the nature of energy absorption following photoelectric and incoherent interactions and the effects of coherent scatter prior to energy deposition by photoelectric interactions. A cascaded systems approach is used to describe the transfer of signal and noise in terms of the modulation transfer function (MTF), Wiener noise power spectrum (NPS), and detective quantum efficiency (DQE). The model is validated by comparing Monte Carlo simulation results with CsI and PbI2 double-Z materials. Excellent agreement is obtained for each metric over the entire diagnostic energy range up to 10 cycles/mm. It is shown that in all cases tested, a combination of two single-Z models weighted by the atomic density of each atom type gives equivalent results to the more comprehensive double-Z model within a few percent. This result suggests the simpler model is adequate and may be preferred for the optimal design of conventional radiography detectors and the estimation of x-ray imaging performance of novel photoconductor materials.

One of the major obstacles toward photon counting detector (PCD)-based clinical x-ray CT systems is the large count rates, because when operated under too intense x-rays, pulse pileup effects (PPEs) due to coincident photons distort the spectrum recorded by PCDs. In this paper we discuss a strategy using a hybrid detector, which consists of PCDs for the central part of the detector [which corresponds to a central small field-of-view (FOV) of the object] and energy integrating detectors (EIDs) for the peripheral part, to achieve the following three goals: 1) to minimize the PPEs; 2) to produce accurate spectral images for the small FOV; and 3) to provide conventional CT images for the entire FOV. The third goal requires a solution to exterior problem, because the central part of EID data is missing. The spectral data obtained by PCDs carry richer information than the intensity data obtained by EIDs; however, performing a simple weighted summation of counts from multi-energy windows of PCD would not produce realistic EID data, as the spectrum recorded by PCD could be skewed by spectral response effects (SREs) and PPEs. We propose a unique approach for the hybrid PCD/EID-CT system in this paper.

Cardiac deformation indices such as strain, strain rate, and time to maximal strain are valuable in early detection of heart disease and hold tremendous prognostic value in assessing patients recovering from heart failure. These indices have been previously measured in modalities such as Doppler echocardiography and magnetic resonance imaging. However, cardiac deformation has not been well characterized in X-ray computed tomography (CT), a modality whose balance of high acquisition speed and good temporal and spatial resolution makes it highly desirable in the clinical setting. The current work, an extension of our group’s previously published cardiac motion estimation algorithm, calculates deformation indices such as strain, strain rate, maximum strain, and time to maximal strain from four-dimensional motion vector field data. Along each dimension, calculations are made between every adjacent pair of grid points, thus striving for simplicity while yielding an increase in spatial resolution over approaches that divide the heart into a number of segments. Results are visualized as semi-transparent color maps superimposed on CT image slices in the short-axis view and the two long-axis views. Results agree with the expected behavior of myocardial contraction. Animal studies are underway to better assess the physiologic accuracy of the calculated deformation indices as well as to compare the results with those from other imaging modalities. The present work and its further refinements may yield rich yet easily accessible information for clinicians in early diagnosis and follow-up monitoring.

Metal artifact is a main cause to degrade CT image quality, but there is still no standard solution to this issue. The cause of introduction of metal artifacts is due to several physical effects, in which beam hardening and noise are two major factors. Accordingly, in this paper these two factors are alleviated by using beam hardening correction based on polynomial fitting and statistical iterative reconstruction based on Poisson log-likelihood approach. Unlike other metal artifact reduction (MAR) methods by using iterative image reconstruction from polychromatic projection dataset, the proposed method in this work does not require a priori knowledge about the X- ray spectrum and attenuations of the materials to be reconstructed. A conventional linear interpolation MAR algorithm and two MAR methods based on beam hardening correction are performed for comparison. Simulation results illustrate that the proposed method can suppress metal artifacts greatly and restore low contrast tissues well.

Scatter remains a major cause of image artifacts in cone beam CT (CBCT). To correct the scatter for improved image reconstruction, the Monte Carlo simulation technique has been useful in estimating the scatter distribution. This technique, however, requires a 3D computational phantom of the patient, which is typically obtained from the reconstructed 3D image and is not fully available for CBCT scans with limited field of view. This study proposes a novel approach to restore the volume of the patient in such cases by use of a standard patient model and image registration techniques. As demonstrated for the 6 x 6 em oral CBCT scan, a full-field image of the model could be registered to the truncated patient image and was then successfully imported to Monte Carlo simulation for scatter estimation. Scatter correction was achieved by subtracting the Monte Carlo scatter data from the raw data on a projection-by-projection basis. Compared to the original data, the reconstructed image with scatter correction showed reduced streak artifacts and an improved contrast resolution of up to 15% between the soft and bony tissue. This approach exploits the low-frequency characteristic of the scatter distribution. The procedure could use more suitable models, and it could in a next step be further automated. It would then be an interesting candidate to improve image quality in practice.

The O-arm system is a mobile intraoperative imaging system that is comprised of fluoroscopy and cone beam CT. The configuration of the O-arm system with absence of patient table and a broad beam width (165 mm in isocenter) brings new practical and physical requirements on how to perform dose measurements. The purpose of this study was to describe a method that overcomes this and makes it possible to characterize the radiation output from the O-arm system. A holder with a clamp and a flexible ball joint that can orientate the radiation detector support and the Mover that can be adjusted to hold the dose detector in a horizontal position was used. Evaluation of the dose response for three different dose detectors of different active length (0.3, 23.1 and 100 mm) was made for three different beam qualities. Furthermore the dose profile free in air to control the possible heel effect and width of the x-ray field during rotation was measured and the dose rate waveform was analyzed. The FWHM of the dose profile was 162 mm. The dose response of the three detectors is reported. The average dose response was lower for the detector with longer active length due to the influence of the dose profile shape. From dynamic measurement total exposure time, pulse width, and the number of pulses were verified. In conclusion, an external horizontal hanging holder with mover option helps to assist to make dose measurement easier and enables characterize the radiation output from the O-arm system.

Often in clinical CT imaging situations, a clinician only requires a small volume of interest (VOI) within aCT slice to be imaged. Unfortunately, due to some fundamental constraints in CT image reconstruction, the entire slice must be irradiated even when a small VOI is all that is clinically required. This produces excess dose for the patient, excess scatter which degrades image quality and increases clinician dose, and may effect patient care because clinicians may limit their use of CT in the interventional setting due to the previous two factors. This paper shows experimental results in which a digital beam attenuator (DBA) is used to modulate the patient dose as a function of view and gantry angle to enhance the SNR in a small VOI relative to the surrounding areas. It was found that the noise was lower by 50% inside the VOI for DBA enabled VOL This promising result was obtained while providing an incident fluence reduction of 13 times on average for all regions not corresponding to the VOI relative to a non-VOI scan.

In this work we applied dose reduction using the prior image constrained compress sensing (DR-PICCS) method on a C-arm cone beam CT system. DR-PICCS uses a smoothed image as the prior image. After applying DRPICCS, the final image will have noise variance inherited from the prior image and spatial resolution from the projection data. In order to investigate the dose reduction of DR-PICCS, three different dose levels were used in C-arm scans of animal subjects using a Siemens Zeego C-arm system under an IACUC protocol. Image volumes were reconstructed using the standard FBP and DR-PICCS algorithms(total of 160 images). These images were randomly mixed and presented to three experienced interventional radiologists(each having more than twenty years reading experience) to review and score using a five-point scale. After statistical significance testing, the results show that DR-PICCS can achieve more than 60% dose reduction while keeping the same image quality. And if we compare FBP and DR-PICCS at the same dose level the results show that DR-PICCS will generate higher quality images.

This work proposed a motion detection method for cone-beam computed tomography (CBCT) that utilizes a calibration phantom of known geometry as the motion detector and an established geometric calibration protocol to provide the motion information. An initial numerical study regarding the consequences of motion and its correction was conducted with a Shepp-Logan and an XCAT phantom. Motion artifacts were induced by acquiring the projections in a simple saddle trajectory scan. Since the scanning trajectory is set, the magnitude of motion for each projection view is already known, the correction of motion can then be efficiently implemented. Motion correction was done prior to the backprojection process of the filtered backprojection (FBP) image reconstruction algorithm. Results showed that motion correction improved the image quality of the reconstructed images. For a known or unknown scanning trajectory, the geometric calibration method can define the geometric information of a scanning system. In the current work, projections of a calibration phantom of known geometry were acquired from a saddle trajectory scan, and geometric parameters for selected projection views were successfully computed from the projection matrix provided by the geometric calibration method. Further studies will involve an experimental investigation wherein a calibration phantom is attached to a randomly moving object and scanned in a circular trajectory. Utilizing the parameters extracted from the geometric calibration, an accurate description of the object motion can be used and adapted for motion correction.

In computed tomography (CT) or conebeam tomography (CBT), filtered backprojection (FBP) has been known as an efficient technique for reconstructing 3D-volumes from acquired projection data. Plain backprojection only would result in systematically blurred objects. To compensate for this blurring, convolution-based filters have been derived that are non-local and sampled with 2048 coefficients or more, dependent on the projection data size. This filtering operation can be classified as finite impulse response (FIR) filtering. In terms of image quality, ideally-derived kernels sometimes amplify too much the high frequency noise (e.g. due to X-ray quantum noise) from the input projections. In practice, regularized filters are often preferred, damping higher frequencies while preserving the sharpness and signal dynamics needed for the reconstructed 3D-objects. From discrete systems theory, another filter type with infinite impulse response (IIR) has been known. Because such a filter recursively uses backward components, it requires very few coefficients while the long-range filter effect is preserved. In the presented work, IIR filters have systematically been designed and tested. They have been adjusted for the correction of a blurring system transfer function as well as for high-frequency noise suppression. Image quality has carefully been inspected by reconstruction of phantom data and clinical cases. It has been found that the filtering step in CBT/FBP can be realized as a recursive filter only, i.e. in self-contained IIRnotation, including adaptions like e.g. apodisation. The number of filtering operations is significantly reduced hereby. So with IIR filtering an efficient alternative for FBP filtering is available.

The steadily growing computational power of modern hardware allows use of more sophisticated reconstruction methods. We present an implementation of the maximum likelihood (ML) method, a previously studied method, for the case of a flat-panel rotational X-ray device. Contrary to the related principle of algebraic reconstruction (ART), the ML method takes into consideration the physical properties of X-radiation, especially the corpuscular character and the associated Poisson distribution of the measured number of photons. The basic principle is the maximization of the joint probability of all measured projections with respect to the attenuation coefficients of all voxels of the object. The application of the ML optimization procedure finally generates an iterative scheme for the update of the attenuation coefficients. For this, in each step an accurate estimation of the forward projections (FP) is mandatory. We use an approximate calculation of the footprints of single voxels based on separable trapezoids. The resulting enormous computational effort is handled by an efficient implementation on GPGPU (General-purpose computing on graphics processing units). As a first look, using data from 133 projections of a sheep head acquired by means of a flat-panel rotational angiography system, we compare the reconstruction by the ML-based method with the gold standard - the Feldkamp filtered back projection (FBP) procedure. The results reveal a clearly reduced amount of streak artifacts as well as less blurring in the statistical reconstruction method.

Cardiac rotational angiography (RA) is well suited for 3-D cardiac imaging during catheter based interventions but remained limited to static images or was characterized by high dose patient radiation dose. We present a new prospective imaging technique that is capable of imaging the dynamics of the cardiac cavities in a single C-arm run during the intervention with a relatively low dose. By combining slow atrial pacing to obtain a stable heart rhythm and a single C-arm rotation with imaging at a regular imaging interval, a prospective 4DRA is established. Pacing interval and imaging framerate can be adapted such that a single cardiac phase is imaged multiple times and a motion free state is imaged from different equiangular positions. A practical implementation of this technique was realized in which the cardiac cavities are imaged while pacing at 105 bpm (574 msec) and imaging at approximately 15 fps. A number of animal experiments were conducted in which the technique was applied and MR imaging was performed subsequently. Quantitative comparison was made by manual contouring of the left ventricle in the RA and MR images of both end-systolic and end-diastolic phases. Reconstructed images of the individual cardiac phases showed all four chambers and important vessels in spite of substantial image noise. 4DRA and MR absolute surface distance errors amounted to 2:8 ± 0:7 mm, which is acceptable. Further, no systematic difference could be identified. Finally, it is expected that the effective dose of a clinical protocol with 381 images will be lower than the current retrospective gated RA protocols.

The feasibility of cone beam CT (CBCT) for differentiating normal epithelium from invasive carcinoma is investigated via a simulation study. The phantom consisted of a 5 mm long 5mm diameter cylinder of a 50:50 mixture of fibrous and fatty tissue. Normal epithelium and invasive carcinoma were each modeled as epithelium and connective tissue compartments with respective cross-sectional dimensions of 158 by 161 μm and 131 by 161 μm . For normal epithelium, 125 cells were placed in the compartments with a higher concentration in the basal layer. For the invasive carcinoma, 314 cells were spread out sporadically. Cells were modeled as 5.67 μm diameter spheres. The attenuation coefficients used in the simulation were those of fat for epithelium, 80:20 mixture of fibrous and fat for the connective tissue and water for cells. A point source and 50 μm detector pixels were assumed. Scatter from the phantom is negligible and was neglected. Three hundred projections were acquired at magnification 10 in vacuum using a 26 kV spectrum. The preliminary study suggest a potential application of CBCT for visualizing cell clusters. The contrast was slightly improved by using a 5 to 10 keV uniform spectrum.

On an onboard cone-beam CT (CBCT) system, the poly-energetic beam generated by current commercial x-ray tubes hardens as it penetrates the object. The beam-hardening effect results in CT image artifacts of up to 100 HU, especially around dense objects (e.g. bones). We propose to insert a half-blocked beam filter between x-ray source and object, such that any ray passing through the object is filtered once from one of the opposite directions in a single full scan. The conventional data processing of dual energy imaging is then applied to obtain material decomposition as well as CT images with no beam-hardening artifacts. In this preliminary study, we demonstrate the method feasibility using computer simulations. The beam filter thickness is optimized to balance the CT number accuracy and the noise level on the reconstructed images via both analytical calculation and measurement of image noise. A calibration phantom is designed to obtain the decomposition function for energy selective imaging by projection measurements without the knowledge of x-ray spectrum and detector response. Using the optimized beam blocker and the calibration phantom, we simulate the data acquisition using scan settings of a commercial CBCT system. Our proposed approach significantly suppresses beam-hardening artifacts and reduces the image error from 65 HU to 9 HU in the selected regions of interest on a head phantom. The method also successfully decomposes bone and soft tissue, with 95% accuracy.

The current Small Animal Radiation Research Platform (SARRP) is poor for localizing small soft tissue targets for irradiation or tumor models growing in a soft tissue environment. Therefore, an imaging method complementary to x-ray CT is required to localize the soft tissue target’s Center of Mass (CoM) to within 1 mm. In this paper, we report the development of an integrated x-ray/bioluminescence imaging/tomography (BLI/BLT) system to provide a pre-clinical, high resolution irradiation system. This system can be used to study radiation effects in small animals under the conebeam computed tomography (CBCT) imaging guidance by adding the bioluminescence imaging (BLI) system as a standalone system which can also be docked onto the SARRP. The proposed system integrates two robotic rotating stages and an x-ray source rated at maximum 130 kVp and having a small variable focal spot. A high performance and low noise CCD camera mounted in a light-tight housing along with an optical filter assembly is used for multiwavelength BL imaging and tomography. A three-mirror arrangement is implemented to eliminate the need of rotating the CCD camera for acquiring multiple views. The mirror system is attached to a motorized stage to capture images in angles between 0-90o (for the standalone system). Camera and CBCT calibration are accomplished.

A reprojection reconstruction is proposed for limited angle cone-beam CT. This approach can be used as an improved method for any non-reprojection method such as total vibration (TV) minimization based and/or projection onto convex sets (POCS) methods in cone-beam CT reconstruction. Since the reprojection and backprojection are mutually inversed operations, the reprojection as line integral can be implemented with backprojector currently used in most CT systems. In this study, we focused on the effect of reprojection reconstruction with a small arc cone-beam CT scan. A human head phantom and a fiber glass plate were used for the study with 15 projections spanning 45° of the scan. The results showed that the ringing artifacts and edge unsharpness are greatly improved by the reprojection reconstruction method. We also found that an arc scan covering larger projection areas of the object would result in a much greater reconstruction result than a scan covering smaller projection areas with and without reprojection reconstruction method.

The motivation of this study is the general lack of knowledge regarding the efficiency and the appropriate use of the adaptation strengths of Siemens automatic exposure control system CARE Dose 4D. The purpose was to evaluate the effect on radiation absorbed dose using different adaptation strengths of CARE Dose 4D in three routine pediatric CT protocols. A pediatric anthropomorphic whole body phantom was used to simulate a 4 year old patient. CT scans were performed with a Siemens SOMATOM Definition Flash using three different pediatric protocols: neck, thorax, and abdomen. The characteristic of the tube current modulation was similar for all adaptation strengths. The difference is the extent of decrease in tube current. The degree of dose reduction using CARE Dose 4D and CARE kV compared using a fix effective mAs was 34-57%, 51-88%, and 56-91% for neck, thorax, and abdomen protocol, respectively. Accordingly, there is a large difference in radiation dose dependent on the adaptation strength: a factor of 1.5, 4.5, and 4.6 for neck, thorax, and abdomen protocol, respectively. The adaptation strengths can be used to obtain user-specified modifications of image quality or radiation dose to the patient. Radiologists and medical physicists need to be aware of the large differences between the adaptation strengths, and such differences are useful when attempting strategies to optimize CT radiation dose.

In this work, we propose three alternative methods to estimate noise map for CT images. Our methods are generalizations to the existing even-and-odd views approach proposed by Hsieh and Thibault [1]. Method one in this work estimates noise map from images reconstructed from three sets of independent views. Method two deals with images reconstructed by using two sets of correlated views. Our method three generates the noise map from two images reconstructed from two sets of independent views while the number of views in each set is unequal. Physical phantom data were employed to validate our proposed noise map estimation methods. In comparison to the existing method, our alternative methods yield reasonably accurate noise map estimation.

Artifacts in computerized tomography (CT), such as metal streak effects, can also be reduced using the iterative reconstruction approach. The main issue in iterative method is the computation cost by efficient implementation of the forward and back-projection operations, which are the dominant cost in all iterative reconstruction algorithms. We designed a field programmable gate array (FPGA)-based operators for iterative forward and back-projection method to solve the artifact model. The projection method in CT reconstruction is to retrieve the volumetric image based on observed projection image and makes reconstruction errors minimize. The FPGA-based operators contain only the iterative reconstruction operations from tomographic projections, and the filtering of detector data and the geometry correction between detector and object are done by host CPU processor. For FPGA design, we used Impulse C package, C-to-FPGA tool including the use of streaming and pipelining for high performance. We evaluated the FPGA-based projection on Shepp-Logan phantom data with metal streak artifact. Simulation results show that the FPGA-based operators can reduce the computation time of iterative reconstruction, while still providing accuracy comparable to CPU or GPU-based reconstruction.

To avoid motion artifacts in medical imaging or to minimize exposure of healthy tissues in radiation therapy medical devices are often synchronized with the patient’s respiration. Today’s respiratory motion monitors require additional effort in preparing the patient, such as mounting of a motion belt or the placement of an optical reflector on the patient breast, and they are not able to measure internal organ motion without implanting markers. An interesting alternative to assess the person’s respiratory motion is a continuous wave Doppler radar. By placing the antennas close to the body, the radar waves propagate into the body and are reflected on boundaries between body tissues, for example between muscle and adipose tissue or on the outline of organs. To evaluate the radar system, a macroscopic simulation model is created to study the radar measurement process of human beings. To check the theoretical considerations of the model, measurements performed by a robot are used. Simulation of human respiratory motion is done by using computed tomography (CT) datasets, reconstructed at different respiratory phases.

In computed tomography (CT) imaging, radiation dose delivered to the patient is one of the major concerns. Many CT developers and researchers have been making efforts to reduce radiation dose. Sparse-view CT takes projections at sparser view-angles and provides a viable option to reducing radiation dose. However, a fast power switching of an x-ray tube, which is needed for the sparse-view sampling, can be challenging in many CT systems. We have recently proposed a novel alternative approach to sparse-view circular CT that can be readily incorporated in the existing CT systems. Instead of switching the x-ray tube power, we proposed to use a multi-slit collimator placed between the x-ray source and the patient to partially block the x-ray beam thereby reducing the radiation. In this study, we performed a simulation study based on numerically acquired projection data to demonstrate a feasibility of using a multi-slit collimator in a helical CT. The XCAT phantom was used and a numerical collimator has been made to apply on the projection data. Numerical multi-slit collimator was designed to have equal size of slit-openings and radio-opaque rectangular areas, and the length dimension of the slits is perpendicular to the rotation axis. For image reconstruction, we used a total-variation minimization (TV) algorithm which has shown its out-performance in many sparse-view CT applications. We demonstrated that the proposed multiple fan-beam helical CT can provide a useful low-dose scanning option.

Tremendous efforts have been devoted to decreasing x-ray radiation dose in diagnostic CT while maintaining the image quality. The statistical noise reduction with iterative algorithm in the projection domain has been one of the major research subjects in CT technologies. Previously, we have proposed a statistical noise reduction with multi-scale decomposition and penalized weighted least square (PWLS) in the projection domain, in which the Markov Random Field (MRF) penalty function is incorporated. In this work, by taking the variation or irregularity of sampling interval along each dimension of the projection domain, we extend our previous method to deal with the situations of incomplete projection data, covering sparse view sampling, latitudinal data truncation and photon starvation. Using the computersimulated projection data of a performance phantom and the FORBILD thorax phantom, we evaluate and verify the performance of the proposed method.

Recently, the Statistical Image Reconstruction (SIR) and compressed sensing (CS) framework has shown promise in the x-ray computed tomography (CT) community. In this paper, we propose to establish an equivalence between the unconstrained optimization problem and a constrained optimization with explicit data consistency term. The immediate consequence of the equivalence is to enable one to use the well-developed optimization method to solve the constrained optimization problem to refine the solution of the corresponding unconstrained optimization problem. As an application of this equivalence, the method was used to develop a convergent and numerically efficient implementation for the prior image constrained compressed sensing (PICCS).

Tomographic microscopy using synchrotron radiation provides high-resolution structure details on the scale of microns. The field of view (FOV) of the microscopy system, however, is usually limited by the detector size. For example, a typical CCD camera used for data acquisition is of size 2048 by 2048. In many cases this CCD camera is not large enough to provide complete information required for accurate reconstruction, and the local tomography problem hereby arises. On the other hand, the huge dataset generated by tomographic microscopy asks for a highly efficient solution with no a priori information necessary. A new padding scheme is therefore proposed for the local tomography issue. It first pads the projection data using the boundary value inside the FOV, which is specified by the detector size, followed by a zero-value padding to 1.5 times the FOV length. The boundary-value padding removes the energy deposition and cupping artifact in reconstruction results from local tomography, while the zero-value padding reduces the drift of the intensity values caused by fully boundary padding. The combination of two padding schemes keeps advantages of fully zero-value padding and fully boundary-value padding, while avoiding their disadvantages. Quantitative analysis using synthetic data shows that the proposed method outperforms fully zero-value padding and fully boundary-value padding in terms of accuracy and ease for post processing. Experimental results for real data are also provided to demonstrate the effectiveness of the proposed method.

In computed tomography, star shape artifacts are introduced by metal objects, which are inside a patient's body. The quality of the reconstructed image can be enhanced by applying a metal artifact reduction method. Unfortunately, a method that removes all such artifacts in order to make the images valuable for medical diagnosis remains to be found. In this study, the influence of metal segmentation is investigated. A thresholding technique, which is the state of the art in the field, is compared with a manual segmentation. Results indicate that a more accurate segmentation can lead to a preservation of important anatomical details, which are of high value for medical diagnosis.

This paper introduces a new strategy to reconstruct computed tomography (CT) images from sparse-view projection data based on total variation stokes (TVS) strategy. Previous works have shown that CT images can be reconstructed from sparse-view data by solving a constrained TV problem. Considering the incompressible property of the voxels along the tangent direction of isophote lines, a tangent vector is consolidated in this newly-proposed algorithm for normal vector estimation. Then, a minimization problem based on this estimated normal vector is addressed and resolved in computation. The to-be-estimated image is obtained by executing this two-step framework iteratively with projection data fidelity constraints. By introducing this normal vector estimation, the edge information of the image is well preserved and the artifacts are efficiently inhibited. In addition, the new proposed algorithm can mitigate the staircase effects which are usually observed from the results of the conventional constrained TV method. In this study, the TVS method was evaluated by patients’ brain raw data which was acquired from Siemens SOMATOM Sensation 16-slice CT scanner. The results suggest that the proposed TVS strategy can accurately reconstruct the brain images and produce comparable results relative to the TV-projection onto convex sets (TV-POCS) method and its general case: adaptiveweighted TV-POCS (AwTV-POCS) method from 232,116 projection views. In addition, an improvement was observed when using only 77 views for TVS method compared to the AwTV/TV-POCS methods. In the quantitative evaluation, the TVS method showed adequate noise-resolution property and highest universal quality index value.

Reducing X-ray exposure to the patients is one of the major research efforts in the computed tomography (CT) field, and one of the common strategies to achieve it is to lower the mAs setting (by lowering the X-ray tube current and/or shortening the exposure time) in currently available CT scanners. However, the image quality from low mAs acquisition is severely degraded due to excessive quantum noise, if no adequate noise control is applied during image reconstruction. Different from filter-based algorithms, statistical reconstruction algorithms model the statistical property of the noise using a cost function and minimize the cost function for an optimal solution in statistical sense. The algorithms have shown to be feasible and effective in both sinogram and image domain. In our previous researches, we proposed penalized reweighted least-squares (PRWLS) approaches to sinogram noise reduction and image reconstruction for low-dose CT imaging, which are in this statistical category. This work is a continuation of the research along this direction and aims to compare the reconstruction quality of two different PRWLS implementations for low-dose cone-beam CT reconstruction: (1) PRWLS sinogram restoration followed by analytical Feldkamp-Davis- Kress reconstruction, (2) fully iterative PRWLS image reconstruction. Inspired by our recent study on the variance of low-mAs projection data in presence of electric noise background, a more accurate weight was adopted in the weighted least-squares term. An anisotropic quadratic form penalty was utilized in both PRWLS implementations to preserve edges during noise reduction. Experiments using the CatPhan® 600 phantom and anthropomorphic head phantom were carried to study the relevant performance of these two implementations on image reconstruction. The results revealed that the implementation (2) can outperform implementation (1) in terms of noise-resolution tradeoff measurement and analysis of the reconstructed small objects due to its matched image edge-preserved penalty in the image domain. However, those gains are offset by the cost of increased computational time. Thus, further examination of real patient data is necessary to show the clinical significance of the iterative PRWLS image reconstruction over the PRWLS sinogram restoration.

Two methods for preventing the deterioration of the accuracy of iterative region-of-interest (ROI) reconstruction are proposed. Both methods apply filters; the first one applies them to the whole region the outside the region of interest (outside ROI) without distinguishing objects (“method 1”, hereafter); and the second one applies them to only the air and patient-table regions while masking other objects outside the ROI (“method 2”). The effectiveness of both methods was evaluated in terms of simulated CT values by using two different phantoms. Method 1 reduced the artifact intensity level by 86% (at most) compared with that obtained with the conventional method. In the case of an object with high attenuation coefficient, method 2 decreases the level more than method 1. In other words, method 2 improves reconstruction accuracy without causing deterioration by the filters. By selecting either method 1 or 2 in accordance with the attenuation coefficient in regions of objects to be imaged, it is possible to reduce the error level compared with the conventional method.

Iterative reconstruction techniques (IRTs) are used to reduce the radiation dose significantly and suppress the noise in computed tomography (CT) imaging. However, the image from IRTs is unacceptable to the human visual system due to the presence of outlier and non-Gaussian noise structure. The conventional noise measurements, such as mean and standard deviation, are limited to provide the information of noise characteristics of an image comprehensively when the undesirable noise structure happens on the image. In this study, the images reconstructed by using Weighted filtered back-projection (WFBP) and image-based IRTs (SAFIRE and SafeCT) were compared in terms of conventional noise statistics, high-order noise statistics, modulation transfer function (MTF), and slice sensitivity profile (SSP) with different levels of radiation dose. The results showed that the noise characteristics, which were considered with conventional and high-order noise statistics, and spatial resolution characteristics were different for the IRTs, reconstruction parameters, and levels of radiation dose. This study can contribute to the optimization of image quality from IRT with the reduction of radiation dose and development of IRT which overcomes the issue caused by undesirable noise structures.

A typical iterative CT reconstruction using SART involves ray-driven forward projection and voxel-driven back- ward projection. Bilinear interpolation is usually applied on image data for forward projection, and linear interpolation is usually applied on projection data for backward projection, when both data are represented using discrete samples in 2D fan-beam geometry. The applied interpolations, however, may affect the spatial resolution, bias and noise properties of the reconstruction. A basis function (such as blob and spline) is therefore applied to formulate a continuous model for the image data to reduce bias. In this paper we propose to apply the blob representation on the projection data and explore its effectiveness. In this way we use continuous model for the data of projection difference during backward projection, and we avoid the linear interpolation in this process. Experimental results show that the proposed scheme is able to provide higher spatial resolution than linear interpolation, while introducing more local variations in the reconstruction. However, the introduced local variations may be reduced with the combination of total variation (TV) minimization. The proposed scheme is therefore able to provide improved spatial resolution while keeping low local variations in reconstructions.

This paper describes a new approach for reconstructing images from a finite number of projections. The rayintegrals of the image f(x, y) are transformed uniquely into the ray-sums of the discrete image f_n,m on the Cartesian lattice. This transformation allows for calculating the tensor representation of the discrete image, when the image is considered as the sum of direction images, or splitting-signals carrying the spectral information of the image at frequency-points of different subsets that cover the Cartesian lattice. These subsets are intersected and this property of redundancy is used to reduce the angular range of projections. The proposed approach is presented for parallel projections and the continuous model. Preliminary results show very good results of image reconstruction when the angular range scanned is 27° and down to 10°.

Dose reduction using prior image constrained compressed sensing (DR-PICCS) is a method of CT reconstruction which utilizes prior image information in a compressed sensing framework to significantly reduce the noise in images acquired at low dose. The purpose of this study was to investigate the impact of edge sharpness and noise level in the prior image data on the resulting DR-PICCS images. Projection data from a 100 rnA CT myocardial perfusion scan of a swine was combined with numerically simulated projections of vessels of varying geometry (diameter = 4, 3, 2 mm) and contrast levels (600, 400, 200 HU enhancement). Bilateral and mean filters were applied to generate prior images, which were then used with the DR-PICCS algorithm. Vessel diameter, effective blurring kernel, and vessel intensity were compared among prior images as well as among the corresponding PICCS images. Although the filters produced prior images with significantly different spatial resolution characteristics at similar noise levels, these differences were mitigated in DR-PICCS images and the DR-PICCS had improved fidelity in comparison to the priors.

The quantitative estimation was performed to verify the effect the low dose imaging with fewer projection data using micro-CT with total variation (TV) minimization method. To assess the image contrast and noise, sparse data were obtained from the projection data of the phantom and the mouse. Filtered-backprojection (FBP) images of the projection data of the phantom and the mouse were used as a reference image reconstructed with 400 projection data. Universal quality index (UQI) was used as an image similarity metric for comparison between TV minimization algorithm and FBP algorithm for both the phantom and the mouse image. Contrast-to-noise ratio (CNR) values for the image derived from TV minimization algorithm with 80-view was approximately 45 % higher than FBP with 400-view up to 10 % iodine solution material. UQI values for the phantom and the mouse images were measured with 0.974 and 0.999, respectively. Low dose image using TV minimization algorithm was proved to be advantageous for micro-CT system. Contrast and noise properties on image from TV minimization at few-view were higher than FBP 80-view and full-view scan. However, CNR from 15 % iodine solution to 20 % iodine solution were lower than FBP due to the lower-intensity of the x-rays. The reconstructed images for both phantom and mouse from TV minimization algorithm were well matched to FBP-reference images.

Statistical CT reconstruction using penalized weighted least-squares(PWLS) criteria can improve image-quality in low-dose CT reconstruction. A suitable design of regularization term can benefit it very much. Recently, sparse representation based on dictionary learning has been treated as the regularization term and results in a high­ quality reconstruction. In this paper, we incorporated a multiscale dictionary into statistical CT reconstruction, which can keep more details compared with the reconstruction based on singlescale dictionary. Further more, we exploited reweigted l₁ norm minimization for sparse coding, which performs better than I norm minimization in locating the sparse solution of underdetermined linear systems of equations. To mitigate the time consuming process that computing the gradiant of regularization term, we adopted the so-called double surrogates method to accelerate ordered-subsets image reconstruction. Experiments showed that combining multiscale dictionary and reweighted l₁ norm minimization can result in a reconstruction superior to that bases on singlescale dictionary and l₁ norm minimization.

Low-dose Computed Tomography (CT) has the benefit of exposing patients to less radiation. However, low dose CT requires special reconstruction techniques to improve the clarity of the image. Unfortunately, these special reconstruction techniques often cannot remove all of the low-dose artifacts. It is important to recognize these artifacts else we run the risk of obscuring important detail or adding false features. In this work, we present a simple scheme which allows us to detect these artifacts. Our technique applies to the specific low-dose CT strategy in which the number of X-ray views taken from the patient is reduced. The first step uses directional interpolation in the low dose sinogram to add more views. While the image created from this interpolated sinogram does not have any artifacts it lacks significantly in clarity due to blurring. Our scheme then compares this image with the image created directly with a low-dose CT reconstruction technique which has better detail but also some remaining artifacts. The comparison reveals these artifacts which we then remove by simple pixel replacement.

Truncation artifacts arise when the object being imaged extends past the scanned field of view (SFOV). The line integrals which lie beyond the SFOV are unmeasured, and reconstruction with traditional filtered backprojection (FBP) produces bright signal artifacts at the edge of the SFOV and little useful information outside the SFOV. A variety of techniques have been proposed to correct for truncation artifacts by estimating the unmeasured rays. We explore an alternative, iterative correction technique that reduces the artifacts and recovers the support (or outline) of the object that is consistent with the measured rays. We assume that the support is filled uniformly with tissue of a given CT number (for example, water-equivalent soft tissue) and segment the region outside the SFOV in a dichotomous fashion into tissue and air. In general, any choice for the object support will not be consistent with the measured rays in that a forward projection of the image containing the proposed support will not match the measured rays. The proposed algorithm reduces this inconsistency by deforming the object support to better match the measured rays. We initialize the reconstruction using the water cylinder extrapolation algorithm, an existing truncation artifact correction technique, but other starting algorithms can be used. The estimate of the object support is then iteratively deformed to reduce the inconsistency with the measured rays. After several iterations, forward projection is used to estimate the missing rays. Preliminary results indicate that this iterative, support recovery technique is able to produce superior reconstructions in the case of significant truncation compared to water cylinder extrapolation.

Development of the indirect scintillating detector is hindered not only by the cost and lead-time of manufacturing but also the computational resources required for numerical modeling. The simulation is bogged down by the number of x-ray photons (gammas) required to duplicate the experimental flood image ensemble necessary to characterize the noise power spectrum (NPS), a key input into the detective quantum efficiency (DQE). The simulation approach presented in this work exploits our previously reported procedure named Fujita-Lubberts- Swank (FLS)6 . This novel technique computes the Lubberts NPS from an ensemble of single gamma point spread functions (PSF) and, as a result, allows for a significant reduction in the number of simulated particles, enabling full DQE(f) simulations with optical transport in less than one CPU-hour. For a given detector and spectrum, the FLS execution time is determined primarily by the number of gamma and optical photons initiated. The optimal number of each varies with the detector specifics. In this work, we present a different simulation paradigm in which Geant4 was customized to allow for the user to specify the quantities of detected gammas, and detected opticals per gamma. These quantities were empirically shown to be constant over a small selection of different detector types. While work still needs to be done to explore the range of detectors for which this technique will work, we demonstrate a concept which brings added convenience and efficiency to FLS detector simulations.

Possible limitations of current dual energy Contrast Enhanced Digital Marnmography(CEDM) are that over­ lapping normal breast tissue structures can obscure the visualization of iodine, and that the only two images acquired provide solution for two variable equations while three variables are required as the breast consists of three materials - adipose and glandular tissues and iodine. To solve this problem with dual energy CEDM, it requires knowledge of the breast thickness at each pixel. However, in many clinical mammography systems employing a spring-loaded paddle, the physical thickness of the breast may not be uniform due to deformation and tilt of the compression paddle. Therefore, we chose to use triple energy CEDM to overcome these limitations, which can provide a third image. However, the radiation dose can remain a major concern due to three exposures. Photon counting detector(PCD) can provide triple energy radiography without mentioned extra exposures. For triple energy CEDM, an iodine quantification method for breast imaging was suggested in this research. We acquired triple energy images of calibration phantom of different iodine concentrations first, using PCD. Then, intensity values at each energy of imaging object could be mapped pixel by pixel to different locations on the calibration phantom images of different iodine thicknesses(concentrations). Interpolation surface of iodine con­ centration was constructed from the mapped locations at each energy. Resultant triple surfaces were combined to find out the intersection of the three iodine thickness surfaces from the three energy images, which tells the estimated iodine thickness from the input intensity value. The result shows that the proposed method could quantify iodine inserts in breast phantom accurately, which simulate lesions in breast filled with different iodine concentrations.

In order to improve the performance of amorphous selenium (a-Se) based detectors, it is beneficial to operate the device at high electric field (≥10 V/μm). Increasing the electric field reduces the ionization energy and increases the hole mobility within the a-Se detector. In order for a practical a-Se detector to be capable of working at a high electric field, injection of holes from the positively biased electrode and injection of electrons from the negatively biased electrode should be prevented. We have investigated different organic materials with high ionization potential as hole-blocking contacts for a-Se based photodetectors. The effect of the organic layer thickness on the dark current and photocurrent performance of the detector was examined. It was found that the injection of holes could be reduced at high electric fields by increasing the thickness of the organic layer.

Detectability of microcalcifications and small lesions in mammography has driven the development of high spatial resolution imagers with small pixel pitch. In this work, we study the detector resolution limits of amorphous selenium (a- Se) with a detailed Monte Carlo transport code for simulation of direct x-ray detectors. The model takes into account generation and re-absorption of characteristic x rays, spreading due to Compton scattering and high-energy secondary electron transport, and drift and diffusion of electron-hole pairs under the applied external electric field. The transport of electron-hole pairs is achieved with a spatiotemporal model that accounts for recombination and trapping of carriers and Coulombic effects of 3D spatial charge distribution. The location information for each detected electron and hole over millions of simulation histories are used to build the detector point response. A range of incident x-ray energies are simulated from 10 to 100 keV. The simulated detector point response can be used to study the spatial resolution characteristics of detectors at different energies ranges and for calculation of the modulation transfer function and image quality metrics.

Protein crystallography is a key method for protein structure investigation in modern medicine and X-ray diffraction detectors are key to performance. We introduced a silicon detector, based on an active-pixel readout of hydrogenated amorphous silicon (a-Si:H) thin film transistors (TFTs) for protein crystallography. In this work, we present the fabrication process of the detector array, performance of the first fabricated TFT arrays, and the performance of the TFTs in terms of fieldeffect mobility, gate material quality, and stability under long stress using a Fe-55 (50 μCi)gamma ray source (6 to 10 keV photon energies). Device fabrication was performed in an in-house facility, Giga-to-Nano microfabrication facility, at the University of Waterloo, and involved plasma enhanced chemical vapor deposition (PECVD) and wet and dry etch techniques with a simple two mask process. The TFT test results promise higher effective field effect mobility of 16.49 cm²/V·s due to the presence of silicon substrate contacting the a-Si:H channel layer along with a compromise in leakage current, yielding a 10⁴ ON/OFF ratio. Meanwhile, the threshold voltage shift is manageable by applying a negative voltage of a duration less than 1/10 of the duty cycle. From the detector leakage test, the leakage current through the TFT gate was acceptable range while the photo-generated current needs to be suppressed with positive voltage bias at the gate electrode. Thus, minimizing the negative gate bias in readout operation is crucial. Finally, TFT readout current under the same Fe-55 X-ray source shows that optimal operation range can be determined when bulk bias is higher than TFT operation bias.

Large penetration depth and weak interaction of high energy X-rays in living organisms provide a non-destructive way to study entire volumes of organs without the need for sophisticated preparation (injection of contrast material, radiotracer labels etc.). X-ray computed tomography (CT) is a powerful diagnostic tool allowing 3D image reconstruction of the complete structure. Using hard X-rays in medical imaging leads to reduced dose received by the patient. At higher energies, however, the conventional scintillators quickly become the limiting factor. They must be thin in order to provide reasonable spatial resolution and preserve image quality. Nevertheless, insufficient thickness introduces the need for long acquisition times due to low stopping power. To address these issues, we synthesized a new structured scintillator to be integrated into CCD- or photodiode-based CT systems. Europiumdoped Lu₂O₃ (Lu₂O₃:Eu) has the highest density among all known scintillators, very high absorption coefficient for X-rays and a bright red emission matching well to the quantum efficiency of the underlying CCD- and photodiode arrays. When coupled to a suitable detector, this microcolumnar scintillator significantly improves the overall detective quantum efficiency of the detector. For the first time ever, structured and scintillating film of Lu2O3:Eu was grown by electron-beam physical vapor deposition. A prototype sensor was produced and evaluated using both laboratory X-ray sources as well as synchrotron radiation. Comparative performance evaluations of the newly developed sensor versus commercial grade scintillators were conducted. Such synthesis of high density, microstructured, scintillating coatings enables the development of high sensitivity X-ray detectors for CT applications.

Previously a-Si:H metal-semiconductor-metal (MSM) lateral detectors for indirect medical imaging applications had been proposed by our research group. These lateral detectors are attractive due to their ease of fabrication primarily because there is no p+ doped semiconductor layer, thus making it compatible with industry standard amorphous silicon thin film transistor electronics processing. However the earlier devices exhibited high dark current which is problematic for integration mode imaging. In the other words, they were limited in term of dynamic range. In this study, we demonstrate an a-Si:H MSM lateral structure with low dark current, high dynamic range and comparable sensitivity and quantum efficiency to conventional p-i-n photodiodes. These improvements are achieved by the introduction of a thin polymer layer as a blocking contact. The fabricated amorphous silicon based MSM detector exhibits a photo-response of more than 3 orders of magnitude to a green light source (λ = 525nm). In comparison to vertical p-i-n structures, the reported MSM lateral devices show gains in terms of dynamic range, ease of fabrication (no p+ layer), faster speed at the cost of a slightly reduced quantum efficiency. The experimental results of dark and photocurrent measurements as well as the responsivity for two in-house fabricated MSM structures at different bias voltages and light intensity are presented. This results are promising and encourage the development of a-Si:H lateral MSM devices for indirect conversion large area medical imaging applications and especially low cost flat panel computed tomography.

The quality of medical images can be characterized by the signal transfer properties of the x-ray converter. Various studies have previously investigated the influence of the detector configuration on the optimization of medical imaging systems. However, novel technologies related to new luminescent materials seem to be promising for further improvements in medical imaging instrumentation technology. The aim of this study was to investigate and optimize granular phosphor-based X-ray converters by examining different phosphor materials with grain size in the nano-scale (four different categories). Optical diffusion was simulated based on Mie scattering theory and the imaging performance was predicted using Monte Carlo simulation methods. The Modulation Transfer Function (MTF) of all cases were evaluated and compared. Results showed and analyzed the relation between phosphor intrinsic properties on optical diffusion. It was found that the resolution of the nanophosphor is directly affected by the optical parameters and becomes better for high values of light extinction factor and light absorption probability. In particular, the present study showed that the utilization of optimum optical parameters based on specific physical (refractive index, light wavelength) and structural (grain size, packing density) parameters enhance manufacturers in nanophopshor synthesis and preparation to follow particular configurations of nanophoshor composition. Finally, high optical modulation was accomplished employing grains of high refractive index and size close to 200 nm.

Powder phosphors scintillators are used in indirect digital radiography as x-ray to light converters coupled to electronic optical sensors (photodiodes, CCDs, CMOS). Recently, nanophosphors have been reported to have enhanced luminescence efficiency. The purpose of the present study was to evaluate Lu₂O₃:Eu nanophosphor as a candidate for digital medical imaging applications. Lu₂O₃:Eu was employed in the form of a 30.2 mg/cm² powder screen with 50 nm grain size and 5% Eu concentration. Both the nanophosphor material and the screen were prepared in our laboratories. Parameters such as the Absolute Efficiency-AE (light energy flux over exposure rate), the Luminescence Efficiency- XLE (Light energy flux over incident x-ray energy flux), Detector Quantum Gain-DQG (optical quanta emitted per incident x-ray quantum) and the light spectral compatibility to electronic optical sensors (Effective Efficiency) were investigated under x-ray excitation in the radiographic energy range. Results were compared with previously published data for a 33.1 mg/cm² Gd₂O₂S:Eu conventional phosphor screen. It was found that Lu₂O₃:Eu nanophosphor has higher AE and XLE by a factor of 1.32 and 1.37 on average, respectively, in the whole radiographic energy range. DQG was also found higher in the energy range from 50 kVp to 100 kVp and comparable thereafter. Effective efficiency was found with high values for electronic optical sensors such as CCDs and CMOS, due to the high spectral compatibility with the upper visible wavelength range. These results indicate that Lu₂O₃:Eu nanophosphor could potentially be considered for applications in digital x-ray radiography detectors.

Due to the relatively high occupational doses associated with interventional and diagnostic fluoroscopy procedures it is important to create awareness about and to quantify the radiation environment that medical staff are exposed to. A computer program was developed to analyze dose data collected from a dosimetry system that uses active personal dosimeters to monitor staff dose in real-time, to obtain an expanded analysis of the radiation environment that clinical staff are exposed to, on a procedural basis. The analyses that are made per procedure and staff member include: accumulated dose μSv, maximum and median dose rate mSv/h, the amount of time a staff member has been exposed to radiation compared to the total fluoroscopy time and the percentage of accumulated dose from 3 different dose rate intervals, including < 0.3 mSv/h, 0.3 - 2.6 mSv/h, and < 2.6 mSv/h. The developed computer program was used to analyze dose data collected from the dosimetry system at the Karolinska University Hospital to study the radiation environment that different categories of staff are exposed to during interventional aorta aneurysm treatment procedures. The analyses have provided the ability to know where to concentrate radiation safety training in interventional and diagnostic fluoroscopy and to ensure that operating rooms are equipped with adequate radiation protection (e.g., radiation protection barriers etc.). The developed computer program and dose data collected from the dosimetry system can be appropriated for other radiation environmental studies in diagnostic x-ray imaging.

A novel dose reduction technique for fluoroscopic interventions involving a combination of a material x-ray region of interest (ROI) attenuator and spatially different, temporally variable ROI temporal recursive filter, was used to guide the catheter to the ROI in three live animal studies, two involving rabbits and one involving a sheep. In the two rabbit studies presented , a catheter was guided to the entrance of the carotid artery. With the added ROI attenuator the image under the high attenuation region is very noisy. By using temporal filtering with a filter weight of 0.6 on previous frames, the noise is reduced. In the sheep study the catheter was guided to the descending aorta of the animal. The sheep offered a relatively higher attenuation to the incident x-rays and thus a higher temporal filter weight of 0.8 on previous frames was used during the procedure to reduce the noise to levels acceptable by the interventionalist. The image sequences from both studies show that significant dose reduction of 5-6 times can be achieved with acceptable image quality outside the ROI by using the above mentioned technique. Even though the temporal filter weighting outside the ROI is higher, the consequent lag does not prevent perception of catheter movement.

We have developed a dose-tracking system (DTS) to manage the risk of deterministic skin effects to the patient during fluoroscopic image-guided interventional cardiac procedures. The DTS calculates the radiation dose to the patient's skin in real-time by acquiring exposure parameters and imaging-system geometry from the digital bus on a Toshiba C-arm unit and displays the cumulative dose values as a color map on a 3D graphic of the patient for immediate feedback to the interventionalist. Several recent updates have been made to the software to improve its function and performance. Whereas the older system needed manual input of pulse rate for dose­ rate calculation and used the CPU clock with its potential latency to monitor exposure duration, each x-ray pulse is now individually processed to determine the skin-dose increment and to automatically measure the pulse rate. We also added a correction for the table pad which was found to reduce the beam intensity to the patient for under-table projections by an additional 5-12% over that of the table alone at 80 kVp for the x-ray filters on the Toshiba system. Furthermore, mismatch between the DTS graphic and the patient skin can result in inaccuracies in dose calculation because of inaccurate inverse-square-distance calculation. Therefore, a means for quantitative adjustment of the patient-graphic-model position and a parameterized patient-graphic library have been developed to allow the graphic to more closely match the patient. These changes provide more accurate estimation of the skin-dose which is critical for managing patient radiation risk.

Low tube current scanning in combination with HYPR (HighlY constrained backPRojection) noise reduction is a proposed method for low-dose time-resolved CT myocardial perfusion imaging. We report animal studies and simulations investigating the coronary angiographic information available in these scans. Four pigs were scanned at 100 rnA and 500 rnA. A HYPR coronary angiographic image was formed from each 100 rnA scan by producing a time-averaged composite image from cardiac cycles centered on the time of peak left ventricular intensity and then multiplying the composite by a weighting image to restore image intensities. Image noise, coronary artery cross sectional area, and coronary artery intensity were measured as a function of the number of beats in the composite, weighting image filtration, and coronary artery size. HYPR images maintained coronary artery area and intensity to within 6-8% of of filtered back projection (FBP) image values, on average, for vessels with cross sectional area greater than 2 mm². Vessel visibility in 100-mA HYPR images was improved relative to 100-mA FBP, in cross sectional and multiplanar reformatted images.

Monte Carlo (MC) simulation based on a patient’s computed tomography (CT) images is a promising way to retroactively determine patient-specific dose from CT scans. CT scans generally include only a portion of the patient’s body; however, photon interactions in regions adjacent to the scan region contribute to the overall scan dose. Thus, the CT images alone, which do not include these adjacent regions, are insufficient for determining dose. In fact, dose underestimation, especially at the scan edge, occurs when the adjacent regions are not accounted for. In this work, the dose underestimation without the scatter region is demonstrated, and the size of the scatter region required to provide sufficient simulated scatter was determined with mathematical phantom studies. For a simple cylindrical water phantom, up to a 25% underestimation of dose was found when no scatter region was used, and a 40 mm scatter region was determined to be required to eliminate this error for scans performed with both the 40 mm and 5 mm collimation sizes. In addition, four different image extrapolation methods based on CT images and scout images were proposed for a chest CT scan of an anthropomorphic phantom. The dose was calculated with the chest images only and the chest images plus the four types of extrapolated images. The results were compared with the dose calculated using whole body images of the anthropomorphic phantom. The image extrapolation methods, especially the ones based on scout images, were shown to improve the dose calculation accuracy under both step-shoot scan mode and helical scan mode. Keywords: CT, patient-specific dose, Monte Carlo, image extrapolation, scout images