| Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ... arXiv preprint arXiv:1811.02629, 2018 | 2170 | 2018 |
| 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 | 1379 | 2023 |
| Segment anything in medical images J Ma, Y He, F Li, L Han, C You, B Wang Nature Communications 15 (1), 654, 2024 | 1359 | 2024 |
| Loss odyssey in medical image segmentation J Ma, J Chen, M Ng, R Huang, Y Li, C Li, X Yang, AL Martel Medical Image Analysis 71, 102035, 2021 | 633 | 2021 |
| The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge N Heller, F Isensee, KH Maier-Hein, X Hou, C Xie, F Li, Y Nan, G Mu, ... Medical image analysis 67, 101821, 2021 | 567 | 2021 |
| Abdomenct-1k: Is abdominal organ segmentation a solved problem? J Ma, Y Zhang, S Gu, C Zhu, C Ge, Y Zhang, X An, C Wang, Q Wang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (10), 6695 …, 2021 | 405 | 2021 |
| Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge VM Campello, P Gkontra, C Izquierdo, C Martin-Isla, A Sojoudi, PM Full, ... IEEE Transactions on Medical Imaging 40 (12), 3543-3554, 2021 | 398 | 2021 |
| U-mamba: Enhancing long-range dependency for biomedical image segmentation J Ma, F Li, B Wang arXiv preprint arXiv:2401.04722, 2024 | 383 | 2024 |
| Towards Efficient COVID-19 CT Annotation: A Benchmark for Lung and Infection Segmentation J Ma, Y Wang, X An, C Ge, Z Yu, J Chen, Q Zhu, G Dong, J He, Z He, ... Medical Physics, 2020 | 347* | 2020 |
| Head and neck tumor segmentation in PET/CT: the HECKTOR challenge V Oreiller, V Andrearczyk, M Jreige, S Boughdad, H Elhalawani, J Castelli, ... Medical image analysis 77, 102336, 2022 | 207 | 2022 |
| Fast and low-GPU-memory abdomen CT organ segmentation: the flare challenge J Ma, Y Zhang, S Gu, X An, Z Wang, C Ge, C Wang, F Zhang, Y Wang, ... Medical Image Analysis 82, 102616, 2022 | 163 | 2022 |
| Unleashing the strengths of unlabelled data in deep learning-assisted pan-cancer abdominal organ quantification: the flare22 challenge J Ma, Y Zhang, S Gu, C Ge, S Mae, A Young, C Zhu, X Yang, K Meng, ... The Lancet Digital Health 6 (11), e815-e826, 2024 | 112* | 2024 |
| How distance transform maps boost segmentation CNNs: an empirical study J Ma, Z Wei, Y Zhang, Y Wang, R Lv, C Zhu, C Gaoxiang, J Liu, C Peng, ... Medical Imaging with Deep Learning, 479-492, 2020 | 102 | 2020 |
| Multi-site infant brain segmentation algorithms: the iSeg-2019 challenge Y Sun, K Gao, Z Wu, G Li, X Zong, Z Lei, Y Wei, J Ma, X Yang, X Feng, ... IEEE Transactions on Medical Imaging 40 (5), 1363-1376, 2021 | 94 | 2021 |
| Graph-mamba: Towards long-range graph sequence modeling with selective state spaces C Wang, O Tsepa, J Ma, B Wang arXiv preprint arXiv:2402.00789, 2024 | 81 | 2024 |
| The multimodality cell segmentation challenge: toward universal solutions J Ma, R Xie, S Ayyadhury, C Ge, A Gupta, R Gupta, S Gu, Y Zhang, G Lee, ... Nature methods, 1-11, 2024 | 71 | 2024 |
| Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: the ADAM challenge KM Timmins, IC van der Schaaf, E Bennink, YM Ruigrok, X An, ... Neuroimage 238, 118216, 2021 | 70 | 2021 |
| Automated segmentation of normal and diseased coronary arteries–the asoca challenge R Gharleghi, D Adikari, K Ellenberger, SY Ooi, C Ellis, CM Chen, R Gao, ... Computerized Medical Imaging and Graphics 97, 102049, 2022 | 63 | 2022 |
| The autopet challenge: towards fully automated lesion segmentation in oncologic pet/ct imaging S Gatidis, M Früh, M Fabritius, S Gu, K Nikolaou, C La Fougère, J Ye, J He, ... | 62 | 2023 |
| Learning geodesic active contours for embedding object global information in segmentation CNNs J Ma, J He, X Yang IEEE Transactions on Medical Imaging 40 (1), 93-104, 2020 | 54 | 2020 |
Bo WangChief AI Scientist,UHN; CIFAR AI Chair, Vector Institute; Assistant Professor, U of Toronto在 vectorinstitute.ai 的电子邮件经过验证
