Mr. Clay S. Didier Profile

Clay S. Didier

at Massachusetts Institute of Technology

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Author

Publications (8)

Proceedings Article | 16 March 2011 Paper

The effect of characteristic x-rays on the spatial and spectral resolution of a CZT-based detector for breast CT

Stephen Glick, Clay Didier

Proceedings Volume 7961, 796110 (2011) https://doi.org/10.1117/12.877784

KEYWORDS: X-rays, Breast, Sensors, X-ray detectors, Photon counting, Spectral resolution, X-ray computed tomography, Imaging systems, Monte Carlo methods, Mammography

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Proceedings Article | 11 March 2009 Paper

Enhanced computer simulation of CT mammography using a flat-panel imager

Clay Didier, J. Michael O'Connor, Yu Chen, Stephen Glick

Proceedings Volume 7258, 72580J (2009) https://doi.org/10.1117/12.813963

KEYWORDS: Sensors, Modulation transfer functions, Monte Carlo methods, Scintillators, Photons, Computer simulations, Breast, Imaging systems, X-rays, Tissues

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Proceedings Article | 18 March 2008 Paper

Quantitative comparison of weighted Feldkamp FBP full-scan and half-scan algorithms for contrast-enhanced CT breast imaging

Clay Didier, Yu Chen, J. Michael O'Connor, Mufeed Mah'D, Stephen Glick

Proceedings Volume 6913, 69133B (2008) https://doi.org/10.1117/12.773395

KEYWORDS: Computed tomography, Sensors, Breast imaging, Tumors, Reconstruction algorithms, Breast cancer, X-ray computed tomography, Monte Carlo methods, Diagnostics, X-rays

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Proceedings Article | 18 March 2008 Paper

Using mastectomy specimens to develop breast models for breast tomosynthesis and CT breast imaging

J. Michael O'Connor, Mini Das, Clay Didier, Mufeed Mah'D, Stephen Glick

Proceedings Volume 6913, 691315 (2008) https://doi.org/10.1117/12.772666

KEYWORDS: Breast, 3D modeling, Systems modeling, X-ray computed tomography, Sensors, Tumor growth modeling, Tissues, Breast imaging, Data modeling, X-rays

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Proceedings Article | 6 March 2008 Paper

Optimizing breast-tomosynthesis acquisition parameters with scanning model observers

H. Gifford, C. Didier, Mini Das, S. Glick

Proceedings Volume 6917, 69170S (2008) https://doi.org/10.1117/12.771018

KEYWORDS: Breast, Tumors, 3D acquisition, Mammography, Tumor growth modeling, 3D modeling, Reconstruction algorithms, 3D image processing, Sensors, Imaging systems

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Proceedings Article | 21 March 2007 Paper

Characterization of a prototype tabletop x-ray CT breast imaging system

J. Michael O'Connor, Stephen Glick, Xing Gong, Clay Didier, Mufeed Mah'd

Proceedings Volume 6510, 65102T (2007) https://doi.org/10.1117/12.713751

KEYWORDS: Modulation transfer functions, X-rays, X-ray computed tomography, Sensors, X-ray imaging, Optical spheres, Breast, Prototyping, Imaging systems, Breast imaging

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Proceedings Article | 19 March 2007 Paper

A computer simulation for evaluating dual-energy contrast-enhanced breast tomosynthesis

Stephen Glick, Clay Didier

Proceedings Volume 6510, 65102V (2007) https://doi.org/10.1117/12.713817

KEYWORDS: Breast, X-rays, Sensors, X-ray imaging, Computer simulations, Iodine, Mammography, Breast imaging, Magnetic resonance imaging, Optical filters

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Proceedings Article | 15 March 2007 Paper

Investigation of the use of iodinated contrast agent in a proposed flat-panel CT mammography system

Clay Didier, Stephen Glick, Xing Gong, Yu Chen, Mufeed Mahd

Proceedings Volume 6510, 651034 (2007) https://doi.org/10.1117/12.713837

KEYWORDS: Tumors, Signal attenuation, Breast, Iodine, X-rays, Mammography, Tissues, X-ray computed tomography, Scattering, Sensors

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In considering a breast CT system, it is important to note that the spectral attenuation profile of a tumor is very similar to that of fibro-glandular tissue. Preliminary evidence based on imaging breast specimens suggest that the CT number of a malignant breast tumor is very similar to that of surrounding fibro-glandular tissue. Therefore, it is expected that radiologists will probably rely more on tumor morphology to distinguish a malignant tumor from fibro-glandular tissue than an increase in contrast per se. Previous studies have shown that iodinated contrast agents can increase the effective attenuation coefficient yielded by a breast tumor thereby providing increased CT tumor contrast. In order to characterize how the intravenous administration of an iodinated contrast agent can affect the performance of CT breast imaging, a computer simulation of such a system was conducted. The two primary goals of this investigation were first to determine how mean glandular dose, choice of x-ray energy spectrum, and iodine contrast agent density affect tumor detection, and second to determine what effect Compton and Rayleigh scattering have on the variability of the attenuation coefficient yielded by CT mammography. The first goal was achieved by making use of a modified version of the Bakic (Med. Phys. 2003) digital breast phantom to model the uncompressed breast, and a 0.5 cm sphere representing a breast tumor was digitally inserted into the ductal region of this phantom. Several projection sets were generated with the tumor containing various densities of iodine contrast agent, different x-ray energy spectra, and different mean glandular dosage (MGD) levels . Slices through the tumor were extracted from the reconstructions of these projections and were used in human observer studies to determine tumor detectability. The second goal was achieved by using the GATE (Geant 4 Application for Tomographic Emission) Monte-Carlo software package to compute the scattering incident on the flat panel detector for an x-ray projection, then using the aforementioned Bakic phantom, a 0.5 cm sphere representing a breast tumor attenuation and a 3.0 mg/ml of Iodinated contrast agent were inserted at various locations with varying attenuation for 100 projection sets with scatter, and 100 projections without scatter. Histograms of the resulting effective attenuation coefficients yielded by Feldkamp filtered backprojection were plotted and compared.

Showing 5 of 8 publications

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