Dr. Xing Gong Profile

Dr. Xing Gong

Research Instructor at Rush Univ Medical Ctr

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Author

Publications (9)

Proceedings Article | 4 March 2008 Paper

Radiation therapy planning using a volumetric 3D display: PerspectaRAD

Joshua Napoli, Sandy Stutsman, James C. H. Chu, Xing Gong, Mark Rivard, Gene Cardarelli, Thomas Ryan, Gregg Favalora

Proceedings Volume 6803, 680312 (2008) https://doi.org/10.1117/12.767896

KEYWORDS: 3D displays, Radiotherapy, 3D volumetric displays, Visualization, Tumors, 3D image processing, Human-machine interfaces, Computed tomography, Cancer

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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 | 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.

Proceedings Article | 2 March 2006 Paper

Optimal spectra for indirect detector breast tomosynthesis

Stephen Glick, Xing Gong

Proceedings Volume 6142, 61421L (2006) https://doi.org/10.1117/12.649547

KEYWORDS: Signal to noise ratio, Sensors, Breast, X-rays, X-ray detectors, Imaging systems, Modulation transfer functions, Mammography, Image quality, Systems modeling

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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

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Proceedings Article | 20 April 2005 Paper

The importance of modeling normal mammographic structure in optimizing flat-panel CT breast imaging systems

Stephen Glick, Samta Thacker, Xing Gong

Proceedings Volume 5745, (2005) https://doi.org/10.1117/12.595538

KEYWORDS: Signal to noise ratio, Breast, Sensors, X-rays, Imaging systems, Mammography, Breast imaging, X-ray detectors, Computed tomography, Systems modeling

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Proceedings Article | 12 May 2004 Paper

Optical coherence tomography: interpretation artifacts and new algorithm

Dirk-Uwe Bartsch, Xing Gong, Cathy Ly, William Freeman

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.535857

KEYWORDS: Optical coherence tomography, Interfaces, Retina, Detection and tracking algorithms, Algorithm development, Eye, Software development, Edge detection, Macula, Reflectivity

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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

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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

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Showing 5 of 9 publications

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