| The importance of skip connections in biomedical image segmentation M Drozdzal, E Vorontsov, G Chartrand, S Kadoury, C Pal International workshop on deep learning in medical image analysis …, 2016 | 1346 | 2016 |
| The liver tumor segmentation benchmark (lits) P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ... Medical Image Analysis 84, 102680, 2023 | 1168 | 2023 |
| Deep learning: a primer for radiologists G Chartrand, PM Cheng, E Vorontsov, M Drozdzal, S Turcotte, CJ Pal, ... Radiographics 37 (7), 2113-2131, 2017 | 1157 | 2017 |
| Magnetic resonance imaging/ultrasound fusion guided prostate biopsy improves cancer detection following transrectal ultrasound biopsy and correlates with multiparametric … PA Pinto, PH Chung, AR Rastinehad, AA Baccala, J Kruecker, ... The Journal of urology 186 (4), 1281-1285, 2011 | 561 | 2011 |
| Intravoxel incoherent motion MR imaging for prostate cancer: An evaluation of perfusion fraction and diffusion coefficient derived from different b‐value combinations Y Pang, B Turkbey, M Bernardo, J Kruecker, S Kadoury, MJ Merino, ... Magnetic resonance in medicine 69 (2), 553-562, 2013 | 297 | 2013 |
| Learning normalized inputs for iterative estimation in medical image segmentation M Drozdzal, G Chartrand, E Vorontsov, M Shakeri, L Di Jorio, A Tang, ... Medical image analysis 44, 1-13, 2018 | 273 | 2018 |
| On orthogonality and learning recurrent networks with long term dependencies E Vorontsov, C Trabelsi, S Kadoury, C Pal International Conference on Machine Learning, 3570-3578, 2017 | 257 | 2017 |
| Liver segmentation: indications, techniques and future directions A Gotra, L Sivakumaran, G Chartrand, KN Vu, F Vandenbroucke-Menu, ... Insights into imaging 8, 377-392, 2017 | 208 | 2017 |
| Robust, accurate and fast automatic segmentation of the spinal cord B De Leener, S Kadoury, J Cohen-Adad Neuroimage 98, 528-536, 2014 | 207 | 2014 |
| Liver lesion segmentation informed by joint liver segmentation E Vorontsov, A Tang, C Pal, S Kadoury 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018 | 168 | 2018 |
| Deep learning workflow in radiology: a primer E Montagnon, M Cerny, A Cadrin-Chênevert, V Hamilton, T Derennes, ... Insights into imaging 11, 1-15, 2020 | 167 | 2020 |
| Multimodality image fusion–guided procedures: technique, accuracy, and applications N Abi-Jaoudeh, J Kruecker, S Kadoury, H Kobeiter, AM Venkatesan, ... Cardiovascular and interventional radiology 35, 986-998, 2012 | 158 | 2012 |
| Sub-cortical brain structure segmentation using F-CNN's M Shakeri, S Tsogkas, E Ferrante, S Lippe, S Kadoury, N Paragios, ... 2016 IEEE 13th international symposium on biomedical imaging (ISBI), 269-272, 2016 | 157 | 2016 |
| D'Amico risk stratification correlates with degree of suspicion of prostate cancer on multiparametric magnetic resonance imaging AR Rastinehad, AA Baccala, PH Chung, JM Proano, J Kruecker, S Xu, ... The Journal of urology 185 (3), 815-820, 2011 | 140 | 2011 |
| Enhancement of accuracy in shape sensing of surgical needles using optical frequency domain reflectometry in optical fibers F Parent, S Loranger, KK Mandal, VL Iezzi, J Lapointe, JS Boisvert, ... Biomedical optics express 8 (4), 2210-2221, 2017 | 137 | 2017 |
| Real-time FDG PET guidance during biopsies and radiofrequency ablation using multimodality fusion with electromagnetic navigation AM Venkatesan, S Kadoury, N Abi-Jaoudeh, EB Levy, R Maass-Moreno, ... Radiology 260 (3), 848-856, 2011 | 127 | 2011 |
| A versatile 3D reconstruction system of the spine and pelvis for clinical assessment of spinal deformities S Kadoury, F Cheriet, C Laporte, H Labelle Medical & biological engineering & computing 45 (6), 591-602, 2007 | 126 | 2007 |
| Deep learning: an update for radiologists PM Cheng, E Montagnon, R Yamashita, I Pan, A Cadrin-Chênevert, ... Radiographics 41 (5), 1427-1445, 2021 | 117 | 2021 |
| Deep learning for automated segmentation of liver lesions at CT in patients with colorectal cancer liver metastases E Vorontsov, M Cerny, P Régnier, L Di Jorio, CJ Pal, R Lapointe, ... Radiology: Artificial Intelligence 1 (2), 180014, 2019 | 116 | 2019 |
| Convolutional networks for kidney segmentation in contrast-enhanced CT scans W Thong, S Kadoury, N Piché, CJ Pal Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2018 | 111 | 2018 |
