| Automated segmentation of prostate zonal anatomy on T2‐weighted (T2W) and apparent diffusion coefficient (ADC) map MR images using U‐Nets F Zabihollahy, N Schieda, S Krishna Jeyaraj, E Ukwatta Medical physics 46 (7), 3078-3090, 2019 | 69 | 2019 |
| Automated classification of solid renal masses on contrast-enhanced computed tomography images using convolutional neural network with decision fusion F Zabihollahy, N Schieda, S Krishna, E Ukwatta European Radiology, 2020 | 62 | 2020 |
| Convolutional neural network‐based approach for segmentation of left ventricle myocardial scar from 3D late gadolinium enhancement MR images F Zabihollahy, JA White, E Ukwatta Medical physics 46 (4), 1740-1751, 2019 | 59 | 2019 |
| Quantitative prostate MRI N Schieda, CS Lim, F Zabihollahy, J Abreu‐Gomez, S Krishna, S Woo, ... Journal of magnetic resonance imaging 53 (6), 1632-1645, 2021 | 56 | 2021 |
| Fully Automated Segmentation of Left Ventricular Scar from 3D Late Gadolinium Enhancement Magnetic Resonance Imaging Using a Cascaded Multi-Planar U-Net (CMPU-Net) F Zabihollahy, M Rajchl, AJ White, E Ukwatta Medical Physics, 2020 | 54 | 2020 |
| Ensemble U‐net‐based method for fully automated detection and segmentation of renal masses on computed tomography images Z Fatemeh, S Nicola, K Satheesh, U Eranga Medical physics 47 (9), 4032-4044, 2020 | 41 | 2020 |
| Detection of COVID-19 from chest x-ray images using transfer learning J Manokaran, F Zabihollahy, A Hamilton-Wright, E Ukwatta Journal of medical imaging 8 (S1), 017503-017503, 2021 | 40 | 2021 |
| Myocardial scar segmentation from magnetic resonance images using convolutional neural network F Zabihollahy, JA White, E Ukwatta Medical Imaging 2018: Computer-Aided Diagnosis 10575, 663-670, 2018 | 35 | 2018 |
| Fully Automated Multi-Organ Segmentation of Female Pelvic Magnetic Resonance Images with Coarse-to-Fine Convolutional Neural Network F Zabihollahy, AN Viswanathan, EJ Schmidt, M Morcos, J Lee Medical Physics, 2021 | 24 | 2021 |
| Fully automated segmentation of clinical target volume in cervical cancer from magnetic resonance imaging with convolutional neural network F Zabihollahy, AN Viswanathan, EJ Schmidt, J Lee Journal of applied clinical medical physics 23 (9), e13725, 2022 | 21 | 2022 |
| Fully automated localization of prostate peripheral zone tumors on apparent diffusion coefficient map MR images using an ensemble learning method F Zabihollahy, E Ukwatta, S Krishna, N Schieda Journal of Magnetic Resonance Imaging 51 (4), 1223-1234, 2020 | 20 | 2020 |
| Deep learning based approach for fully automated detection and segmentation of hard exudate from retinal images F Zabihollahy, A Lochbihler, E Ukwatta Medical imaging 2019: Biomedical applications in molecular, structural, and …, 2019 | 20 | 2019 |
| Machine Learning-based Segmentation of Left Ventricular Myocardial Fibrosis from Magnetic Resonance Imaging F Zabihollahy, S Rajan, E Ukwatta Current Radiology Reports, 2020 | 17 | 2020 |
| Fully automated segmentation of left ventricular myocardium from 3D late gadolinium enhancement magnetic resonance images using a U-net convolutional neural network-based model F Zabihollahy, JA White, E Ukwatta Medical Imaging 2019: Computer-Aided Diagnosis 10950, 832-839, 2019 | 15 | 2019 |
| Continuous monitoring of mechanical properties of plantar soft tissue for diabetic patients using wearable ultrasonic and force sensors F Zabihollahy, BM Trindade, Y Ono, ED Lemaire 2016 IEEE EMBS International Student Conference (ISC), 1-4, 2016 | 8 | 2016 |
| Evaluation of spatial attentive deep learning for automatic placental segmentation on longitudinal MRI Y Liu, F Zabihollahy, R Yan, B Lee, C Janzen, SU Devaskar, K Sung Journal of Magnetic Resonance Imaging 57 (5), 1533-1540, 2023 | 7 | 2023 |
| Virtual electrophysiological study as a tool for evaluating efficacy of MRI techniques in predicting adverse arrhythmic events in ischemic patients E Ukwatta, P Nikolov, F Zabihollahy, NA Trayanova, GA Wright Physics in Medicine & Biology 63 (22), 225008, 2018 | 7 | 2018 |
| Transfer learning-based approach for automated kidney segmentation on multiparametric MRI sequences R Gaikar, F Zabihollahy, MW Elfaal, A Azad, N Schieda, E Ukwatta Journal of Medical Imaging 9 (3), 036001-036001, 2022 | 6 | 2022 |
| Patch-Based Convolutional Neural Network for Differentiation of Cyst from Solid Renal Mass on Contrast-Enhanced Computed Tomography Images F Zabihollahy, N Schieda, E Ukwatta IEEE ACCESS, 1-8, 2020 | 6 | 2020 |
| 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 | 3 | 2022 |
Eranga UkwattaAssociate Professor, School of Engineering, University of GuelphVerified email at uoguelph.ca
