Dr. Mufeed M. Mahmoud Profile

Dr. Mufeed M. Mahmoud

Assistant Professor at Univ of Massachusetts Lowell

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Publications (8)

Proceedings Article | 8 February 2017 Presentation + Paper

Impact of anatomical parameters on optical coherence tomography retinal nerve fiber layer thickness abnormality patterns

Neda Baniasadi, Mengyu Wang, Hui Wang, Qingying Jin, Mufeed Mahd, Tobias Elze

Proceedings Volume 10045, 100450P (2017) https://doi.org/10.1117/12.2251435

KEYWORDS: Optical coherence tomography, Nerve, Arteries, Visualization, Manufacturing, Eye, Diagnostics, Optic nerve, Head, Medical imaging

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Proceedings Article | 21 March 2014 Paper

Enhancement of 3D modeling and classification of microcalcifications in breast computed tomography (BCT)

Hiam Alquran, Eman Shaheen, J. Michael O'Connor, Mufeed Mahd

Proceedings Volume 9034, 903436 (2014) https://doi.org/10.1117/12.2043277

KEYWORDS: 3D modeling, Breast, Computer aided diagnosis and therapy, Radon transform, 3D image processing, Image classification, Mammography, Computed tomography, Cancer, Breast cancer

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Proceedings Article | 3 March 2012 Paper

Comparing human observer performance in detecting microcalcifications with energy weighting and photon counting breast CT

Kesava Kalluri, Mufeed Mahd, Stephen Glick

Proceedings Volume 8313, 83130B (2012) https://doi.org/10.1117/12.911720

KEYWORDS: Sensors, Breast, Photon counting, Signal to noise ratio, X-rays, Computer simulations, Tissues, X-ray computed tomography, X-ray detectors, Signal attenuation

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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 | 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 | 26 July 2004 Paper

An FTCS subject to random actuator failures and plant parameter uncertainties

Mufeed Mahmoud

Proceedings Volume 5383, (2004) https://doi.org/10.1117/12.546063

KEYWORDS: Actuators, Control systems, Matrices, Feedback control, Stochastic processes, Detection and tracking algorithms, Algorithms, Computing systems, Modeling, Systems modeling

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Showing 5 of 8 publications

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