| 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 | 1276 | 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 | 607 | 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 | 398 | 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 | 223 | 2022 |
| 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 | 111 | 2023 |
| 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 | 106 | 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 | 65 | 2023 |
| 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 | 55 | 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 | 52 | 2021 |
| 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, ... arXiv preprint arXiv:2203.12362, 2022 | 50 | 2022 |
| 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 | 46 | 2019 |
| 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 | 32 | 2020 |
| 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 | 25 | 2023 |
| Improving splenomegaly segmentation by learning from heterogeneous multi-source labels Y Tang, Y Huo, Y Xiong, H Moon, A Assad, TK Moyo, MR Savona, ... Medical Imaging 2019: Image Processing 10949, 53-60, 2019 | 22 | 2019 |
| 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 | 20 | 2019 |
| More knowledge is better: Cross-modality volume completion and 3D+ 2D segmentation for intracardiac echocardiography contouring H Liao, Y Tang, G Funka-Lea, J Luo, SK Zhou Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 20 | 2018 |
| UNETR: transformers for 3D medical image segmentation (2021) A Hatamizadeh, Y Tang, V Nath, D Yang, A Myronenko, B Landman, ... arXiv preprint arXiv:2103.10504, 0 | 18 | |
| 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 | 17 | 2021 |
| Semi-supervised multi-organ segmentation through quality assurance supervision HH Lee, Y Tang, O Tang, Y Xu, Y Chen, D Gao, S Han, R Gao, ... Medical Imaging 2020: Image Processing 11313, 363-369, 2020 | 16 | 2020 |
| Contrast phase classification with a generative adversarial network Y Tang, HH Lee, Y Xu, O Tang, Y Chen, D Gao, S Han, R Gao, ... Medical Imaging 2020: Image Processing 11313, 220-227, 2020 | 15 | 2020 |
Bennett Allan LandmanElectrical and Computer Engineering, Vanderbilt UniversityПотвърден имейл адрес: vanderbilt.edu
