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Nadia A. Farrag
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Evaluation of fully automated myocardial segmentation techniques in native and contrast‐enhanced T1‐mapping cardiovascular magnetic resonance images using fully convolutional …
NA Farrag, A Lochbihler, JA White, E Ukwatta
Medical Physics 48 (1), 215-226, 2021
182021
Effect of T1‐mapping technique and diminished image resolution on quantification of infarct mass and its ability in predicting appropriate ICD therapy
NA Farrag, V Ramanan, GA Wright, E Ukwatta
Medical physics 45 (4), 1577-1585, 2018
102018
Semi-automated myocardial segmentation in native T1-mapping CMR using deformable non-rigid registration of CINE images
NA Farrag, JA White, E Ukwatta
Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and …, 2019
42019
Transfer learning based fully automated kidney segmentation on MR images
R Gaikar, F Zabihollahy, N Farrag, MW Elfaal, N Schieda, E Ukwatta
Medical Imaging 2022: Biomedical Applications in Molecular, Structural, and …, 2022
22022
Assessment of left atrial fibrosis progression in canines following rapid ventricular pacing using 3D late gadolinium enhanced CMR images
NA Farrag, RE Thornhill, FS Prato, AC Skanes, R Sullivan, D Sebben, ...
Plos one 17 (7), e0269592, 2022
12022
Semi-automated myocardial segmentation of T1-mapping cardiovascular magnetic resonance images using deformable non-rigid registration from CINE images.
NA Farrag, JA White, E Ukwatta
Medical Imaging: Biomedical Applications in Molecular, Structural, and …, 2019
12019
Automated myocardial segmentation of extra-cellular volume mapping cardiac magnetic resonance images using fully convolutional neural networks
NA Farrag, S Bhagavan, D Sebben, P Ruwanpura, JA White, E & Ukwatta
SPIE Medical Imaging 12036 (29), 1-8, 2022
2022
Image Processing Techniques for Analysis of Myocardial Fibrosis and Related Cardiomyopathies in Cardiac Magnetic Resonance Imaging
N Farrag
Carleton University, 2022
2022
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