| M-net: A convolutional neural network for deep brain structure segmentation R Mehta, J Sivaswamy 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017 | 185 | 2017 |
| BrainSegNet: a convolutional neural network architecture for automated segmentation of human brain structures R Mehta, A Majumdar, J Sivaswamy Journal of Medical Imaging 4 (2), 024003-024003, 2017 | 90 | 2017 |
| 3D U-Net for brain tumour segmentation R Mehta, T Arbel International MICCAI Brainlesion Workshop, 254-266, 2018 | 55 | 2018 |
| QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation--Analysis of Ranking Scores and Benchmarking Results R Mehta, A Filos, U Baid, C Sako, R McKinley, M Rebsamen, K Dätwyler, ... Journal of Machine Learning for Biomedical Imaging (MELBA). 2022:026, 2022 | 32 | 2022 |
| RS-Net: Regression-segmentation 3D CNN for synthesis of full resolution missing brain MRI in the presence of tumours R Mehta, T Arbel Simulation and Synthesis in Medical Imaging: Third International Workshop …, 2018 | 28 | 2018 |
| Construction of Indian Human Brain Atlas J Sivaswamy, AJ Thottupattu, R Mehta, R Sheelakumari, C Kesavadas Neurology India 67 (1), 229, 2019 | 27 | 2019 |
| Propagating uncertainty across cascaded medical imaging tasks for improved deep learning inference R Mehta, T Christinck, T Nair, A Bussy, S Premasiri, M Costantino, ... IEEE Transactions on Medical Imaging, 2021 | 24 | 2021 |
| Uncertainty Evaluation Metric for Brain Tumour Segmentation R Mehta, A Filos, Y Gal, T Arbel Medical Imaging with Deep Learning (MIDL) 2020 short papers, 2020 | 20 | 2020 |
| Had-net: A hierarchical adversarial knowledge distillation network for improved enhanced tumour segmentation without post-contrast images S Vadacchino, R Mehta, NM Sepahvand, B Nichyporuk, JJ Clark, T Arbel Medical Imaging with Deep Learning, 787-801, 2021 | 17 | 2021 |
| Propagating uncertainty across cascaded medical imaging tasks for improved deep learning inference R Mehta, T Christinck, T Nair, P Lemaitre, D Arnold, T Arbel Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and …, 2019 | 17 | 2019 |
| Improving pathological structure segmentation via transfer learning across diseases B Kaur, P Lemaître, R Mehta, NM Sepahvand, D Precup, D Arnold, ... Domain Adaptation and Representation Transfer and Medical Image Learning …, 2019 | 15 | 2019 |
| You Only Need a Good Embeddings Extractor to Fix Spurious Correlations R Mehta, V Albiero, L Chen, I Evtimov, T Glaser, Z Li, T Hassner European Conference on Computer Vision Workshops (ECCVw), 2022 | 10 | 2022 |
| Information gain sampling for active learning in medical image classification R Mehta, C Shui, B Nichyporuk, T Arbel International Workshop on Uncertainty for Safe Utilization of Machine …, 2022 | 7 | 2022 |
| Rethinking Generalization: The Impact of Annotation Style on Medical Image Segmentation B Nichyporuk, J Cardinell, J Szeto, R Mehta, JPR Falet, DL Arnold, ... Journal of Machine Learning for Biomedical Imaging (MELBA). 2022:029, 2022 | 6 | 2022 |
| Evaluating the fairness of deep learning uncertainty estimates in medical image analysis R Mehta, C Shui, T Arbel Medical Imaging with Deep Learning, 1453-1492, 2023 | 5 | 2023 |
| Sub-cortical structure segmentation database for young population J Sivaswamy, AJ Thottupattu, V Mythri, R Mehta, R Sheelakumari, ... arXiv preprint arXiv:2111.01561, 2021 | 4 | 2021 |
| Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation B Nichyporuk, J Cardinell, J Szeto, R Mehta, S Tsaftaris, DL Arnold, ... Domain Adaptation and Representation Transfer, and Affordable Healthcare and …, 2021 | 4 | 2021 |
| Mitigating Calibration Bias Without Fixed Attribute Grouping for Improved Fairness in Medical Imaging Analysis C Shui, J Szeto, R Mehta, DL Arnold, T Arbel International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 3 | 2023 |
| Population specific template construction and brain structure segmentation using deep learning methods R Mehta International Institute of Information Technology Hyderabad, 2017 | 3 | 2017 |
| Debiasing Counterfactuals in the Presence of Spurious Correlations A Kumar, N Fathi, R Mehta, B Nichyporuk, JPR Falet, S Tsaftaris, T Arbel Workshop on Clinical Image-Based Procedures, 276-286, 2023 | 2 | 2023 |
Tal ArbelProfessor of Electrical & Computer Engineering, McGill UniversityVerified email at cim.mcgill.ca
