Ms. Aruna A. Vedula Profile

Aruna A. Vedula

Research Assistant at Univ of Massachusetts

SPIE Involvement:

Author

Publications (3)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 20 April 2005 Paper

A comparison of lesion detection accuracy using digital mammography and flat-panel CT breast imaging

Xing Gong, Aruna Vedula, Samta Thacker, Stephen Glick

Proceedings Volume 5745, (2005) https://doi.org/10.1117/12.594955

KEYWORDS: Breast, Imaging systems, Mammography, 3D modeling, Tissues, Breast imaging, Computer simulations, X-ray computed tomography, Digital mammography, X-rays

Read Abstract +

Although conventional mammography is currently the best modality to detect early breast cancer, it is limited in that the recorded image represents the superposition of a 3D object onto a 2D plane. As an alternative, cone-beam CT breast imaging with a CsI based flat-panel imager (CTBI) has been proposed with the ability to provide 3D visualization of breast tissue. To investigate possible improvements in lesion detection accuracy using CTBI over digital mammography (DM), a computer simulation study was conducted using simulated lesions embedded into a structured 3D breast model. The computer simulation realistically modeled x-ray transport through a breast model, as well as the signal and noise propagation through the flat-panel imager. Polyenergetic x-ray spectra of W/Al 50 kVp for CTBI and Mo/Mo 28 kVp for DM were modeled. For the CTBI simulation, the intensity of the x-ray spectra for each projection view was determined so as to provide a total mean glandular dose (MGD) of 4 mGy, which is approximately equivalent to that given in a conventional two-view screening mammography study. Since only one DM view was investigated here, the intensity of the DM x-ray spectra was defined to give 2 mGy MGD. Irregular lesions were simulated by using a stochastic growth algorithm providing lesions with an effective diameter of 5 mm. Breast tissue was simulated by generating an ensemble of backgrounds with a power law spectrum. To evaluate lesion detection accuracy, a receiver operating characteristic (ROC) study was performed with 4 observers reading an ensemble of images for each case. The average area under the ROC curves (A_z) was 0.94 for CTBI, and 0.81 for DM. Results indicate that a 5 mm lesion embedded in a structured breast phantom can be detected by CT breast imaging with statistically significant higher confidence than with digital mammography.

Proceedings Article | 4 May 2004 Paper

Using LROC analysis to evaluate detection accuracy of microcalcification clusters imaged with flat-panel CT mammography

Xing Gong, Stephen Glick, Aruna Vedula

Proceedings Volume 5372, (2004) https://doi.org/10.1117/12.535576

KEYWORDS: Sensors, Mammography, X-rays, Breast, X-ray computed tomography, Target detection, X-ray optics, Optical spheres, Signal detection, Reconstruction algorithms

Read Abstract +

The purpose of this study is to investigate the detectability of microcalcification clusters (MCCs) using CT mammography with a flat-panel detector. Compared with conventional mammography, CT mammography can provide improved discrimination between malignant and benign cases as it can provide the radiologist with more accurate morphological information on MCCs. In this study, two aspects of MCC detection with flat-panel CT mammography were examined: (1) the minimal size of MCCs detectable with mean glandular dose (MGD) used in conventional mammography; (2) the effect of different detector pixel size on the detectability of MCCs. A realistic computer simulation modeling x-ray transport through the breast, as well as both signal and noise propagation through the flat-panel imager, was developed to investigate these questions. Microcalcifications were simulated as calcium carbonate spheres with diameters set at the levels of 125, 150 and 175 μm. Each cluster consisted of 10 spheres spread randomly in a 6×6 mm² region of interest (ROI) and the detector pixel size was set to 100×100, 200×200, or 300×300μm². After reconstructing 100 projection sets for each case (half with signal present) with the cone-beam Feldkamp (FDK) algorithm, a localization receiver operating characteristic (LROC) study was conducted to evaluate the detectability of MCCs. Five observers chose the locations of cluster centers with correspondent confidence ratings. The average area under the LROC curve suggested that the 175 μm MCCs can be detected at a high level of confidence. Results also indicate that flat-panel detectors with pixel size of 200×200 μm² are appropriate for detecting small targets, such as MCCs.

Proceedings Article | 5 June 2003 Paper

Computer simulation of CT mammography using a flat-panel imager

Aruna Vedula, Stephen Glick, Xing Gong

Proceedings Volume 5030, (2003) https://doi.org/10.1117/12.480015

KEYWORDS: Sensors, X-rays, Mammography, Signal attenuation, Imaging systems, Breast, Signal to noise ratio, X-ray detectors, Monte Carlo methods, Scintillators

Read Abstract +

Software has been developed to simulate a cone-beam CT mammography imaging system that consists of an x-ray tube and a flat-panel detector that rotate simultaneously around the pendant breast. The simulation uses an analytical expression or ray-tracing to generate projection sets of breast phantoms at 1 keV intervals dictated by the input x-ray energy spectra. The x-ray focal spot was modeled as having a Gaussian distribution. The detector was modeled as an amorphous silicon (aSi:H) flat-panel imager that uses a structured CsI scintillator. Noise propagation through the detector was simulated by modeling statistical variations of the projection images at each energy interval as a scaled Poisson process. Scintillator blurring was simulated by using an empirically determined modulation transfer function. After introducing noise and detector blur, projection sets simulated at each energy were then combined and reconstructed using Feldkamp's cone-beam reconstruction algorithm. Using this framework, the effects of a number of acquisition and reconstruction parameters can be investigated. Some examples are shown including the impact of the kVp setting and the number of projection angles on the reconstructed image.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years