| Unetr: Transformers for 3d medical image segmentation A Hatamizadeh, Y Tang, V Nath, D Yang, A Myronenko, B Landman, ... Proceedings of the IEEE/CVF winter conference on applications of computer …, 2022 | 2067 | 2022 |
| Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images A Hatamizadeh, V Nath, Y Tang, D Yang, HR Roth, D Xu International MICCAI brainlesion workshop, 272-284, 2021 | 1139 | 2021 |
| Self-supervised pre-training of swin transformers for 3d medical image analysis Y Tang, D Yang, W Li, HR Roth, B Landman, D Xu, V Nath, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 663 | 2022 |
| Monai: An open-source framework for deep learning in healthcare MJ Cardoso, W Li, R Brown, N Ma, E Kerfoot, Y Wang, B Murrey, ... arXiv preprint arXiv:2211.02701, 2022 | 497 | 2022 |
| Segment anything model (sam) for digital pathology: Assess zero-shot segmentation on whole slide imaging R Deng, C Cui, Q Liu, T Yao, LW Remedios, S Bao, BA Landman, ... arXiv preprint arXiv:2304.04155, 2023 | 192 | 2023 |
| Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives J Li, J Chen, Y Tang, C Wang, BA Landman, SK Zhou Medical image analysis 85, 102762, 2023 | 191 | 2023 |
| Clip-driven universal model for organ segmentation and tumor detection J Liu, Y Zhang, JN Chen, J Xiao, Y Lu, B A Landman, Y Yuan, A Yuille, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 156 | 2023 |
| Proceedings of the IEEE/CVF winter conference on applications of computer vision A Hatamizadeh, Y Tang, V Nath, D Yang, A Myronenko, B Landman IEEE, 2022 | 120 | 2022 |
| Monai label: A framework for ai-assisted interactive labeling of 3d medical images A Diaz-Pinto, S Alle, V Nath, Y Tang, A Ihsani, M Asad, F Pérez-García, ... Medical Image Analysis 95, 103207, 2024 | 78 | 2024 |
| Deterministic inverse design of Tamm plasmon thermal emitters with multi-resonant control M He, JR Nolen, J Nordlander, A Cleri, NS McIlwaine, Y Tang, G Lu, ... Nature materials 20 (12), 1663-1669, 2021 | 72 | 2021 |
| High-resolution 3D abdominal segmentation with random patch network fusion Y Tang, R Gao, HH Lee, S Han, Y Chen, D Gao, V Nath, C Bermudez, ... Medical image analysis 69, 101894, 2021 | 64 | 2021 |
| Unest: local spatial representation learning with hierarchical transformer for efficient medical segmentation X Yu, Q Yang, Y Zhou, LY Cai, R Gao, HH Lee, T Li, S Bao, Z Xu, ... Medical Image Analysis 90, 102939, 2023 | 57 | 2023 |
| Distanced LSTM: Time-distanced gates in long short-term memory models for lung cancer detection R Gao, Y Huo, S Bao, Y Tang, SL Antic, ES Epstein, AB Balar, S Deppen, ... Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019 …, 2019 | 56 | 2019 |
| Swinunetr-v2: Stronger swin transformers with stagewise convolutions for 3d medical image segmentation Y He, V Nath, D Yang, Y Tang, A Myronenko, D Xu International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 46 | 2023 |
| Time-distanced gates in long short-term memory networks R Gao, Y Tang, K Xu, Y Huo, S Bao, SL Antic, ES Epstein, S Deppen, ... Medical image analysis 65, 101785, 2020 | 35 | 2020 |
| All-in-sam: from weak annotation to pixel-wise nuclei segmentation with prompt-based finetuning C Cui, R Deng, Q Liu, T Yao, S Bao, LW Remedios, BA Landman, Y Tang, ... Journal of Physics: Conference Series 2722 (1), 012012, 2024 | 34 | 2024 |
| Abdomenatlas-8k: Annotating 8,000 CT volumes for multi-organ segmentation in three weeks C Qu, T Zhang, H Qiao, Y Tang, AL Yuille, Z Zhou Advances in Neural Information Processing Systems 36, 2024 | 30 | 2024 |
| Body part regression with self-supervision Y Tang, R Gao, S Han, Y Chen, D Gao, V Nath, C Bermudez, MR Savona, ... IEEE transactions on medical imaging 40 (5), 1499-1507, 2021 | 24 | 2021 |
| Stochastic tissue window normalization of deep learning on computed tomography Y Huo, Y Tang, Y Chen, D Gao, S Han, S Bao, S De, JG Terry, JJ Carr, ... Journal of Medical Imaging 6 (4), 044005-044005, 2019 | 22 | 2019 |
| Improving splenomegaly segmentation by learning from heterogeneous multi-source labels Y Tang, Y Huo, Y Xiong, H Moon, A Assad, TK Moyo, MR Savona, ... Proceedings of Spie--the International Society for Optical Engineering 10949, 2019 | 21 | 2019 |
Bennett Allan LandmanElectrical and Computer Engineering, Vanderbilt UniversityEmail confirmado em vanderbilt.edu
