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Medical Image Segmentation

Surveys

  • Foundation Models for Biomedical Image Segmentation: A Survey, Ho Hin Lee*, Yu Gu*, Theodore Zhao, Yanbo Xu, Jianwei Yang, Naoto Usuyama, Cliff Wong, Mu Wei, Bennett A. Landman, Yuankai Huo, Alberto Santamaria-Pang, Hoifung Poon [Paper]

Year 2024

  • SegmentAnyBone: A Universal Model that Segments Any Bone at Any Location on MRI, Hanxue Gu et al. [Paper] [Code]

  • [AAAI-2024] Learning Generalized Medical Image Segmentation from Decoupled Feature Queries, Qi Bi; Jingjun Yi; Hao Zheng; Wei Ji; Yawen Huang; Yuexiang Li; Yefeng Zheng [Github]

  • [AAAI-2024] DTMFormer: Dynamic Token Merging for Boosting Transformer-Based Medical Image Segmentation, Zhehao Wang; Xian Lin; Nannan Wu; Li Yu; Kwang-Ting Cheng; Zengqiang Yan

  • [AAAI-2024] MedSegDiff-V2: Diffusion-based Medical Image Segmentation with Transformer, Junde Wu; Wei Ji; Huazhu Fu; Min Xu; Yueming Jin; Yanwu Xu [Paper] [Github]

Year 2023

  • MedSegDiff-V2: Diffusion based Medical Image Segmentation with Transformer, Junde Wu1,6,7,8, Wei Ji2, Huazhu Fu3, Min Xu*,4,6 Yueming Jin1, Yanwu Xu [Paper] [Code]

  • Chen, Jieneng, et al. "Transunet: Transformers make strong encoders for medical image segmentation." arXiv preprint arXiv:2102.04306 (2021). [Paper] [Code]

  • Chen, Jieneng, et al. "3D TransUNet: Advancing Medical Image Segmentation through Vision Transformers." arXiv preprint arXiv:2310.07781 (2023). [Paper] [Code]

Year 2022

Year 2021