Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
368-02-002 ISMRM Abstract

LLM-Enhanced Multi-modal Network for Tibiofemoral Joint Tissue Segmentation in Knee MRI

Primary: Analysis Methods - Segmentation and Detection
Secondary: Analysis Methods - Multi-Modal Learning with LLMs/VLMs
368-02-002 · Segmentation for Musculoskeletal MRI Applications · Monday, 11 May, 9:15 AM–10:10 AM · Digital Posters Row I
Keywords: Large Language Models Automated segmentation Multi-modal Vision-language model
Accepted
Lu Wen 1, Junru Zhong1, Weitian Chen1
1CU Lab of AI in Radiology (CLAIR), Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, China
Presenting Author: Lu Wen

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References

1. Liu, Q., Xu, Z., Jiao, Y., & Niethammer, M. (2022, September). isegformer: interactive segmentation via transformers with application to 3d knee mr images. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 464-474). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-16443-9_45 [doi]
2. Wang, X., & Shi, C. (2025). Patch Attention U-Net for knee cartilage segmentation in magnetic resonance images. Biomedical Signal Processing and Control, 106, 107754. https://doi.org/10.1016/j.bspc.2025.107754 [doi]
3. Li, Z., Li, Y., Li, Q., Wang, P., Guo, D., Lu, L., ... & Hong, Q. (2023). Lvit: language meets vision transformer in medical image segmentation. IEEE transactions on medical imaging, 43(1), 96-107. https://doi.org/10.1109/TMI.2023.3291719 [doi]
4. Koleilat, T., Asgariandehkordi, H., Rivaz, H., & Xiao, Y. (2024, October). Medclip-sam: Bridging text and image towards universal medical image segmentation. In International conference on medical image computing and computer-assisted intervention (pp. 643-653). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-72390-2_60 [doi]
5. Yao, Y., Zhong, J., Zhang, L., Khan, S., & Chen, W. (2024). CartiMorph: A framework for automated knee articular cartilage morphometrics. Medical Image Analysis, 91, 103035. https://doi.org/10.1016/j.media.2023.103035 [doi]
6. Ronneberger, O., Fischer, P., & Brox, T. (2015, October). U-net: Convolutional networks for biomedical image segmentation. In International Conference on Medical image computing and computer-assisted intervention (pp. 234-241). Cham: Springer international publishing. https://doi.org/10.1007/978-3-319-24574-4_28 [doi]
7. Lee, J., Yoon, W., Kim, S., Kim, D., Kim, S., So, C. H., & Kang, J. (2020). BioBERT: a pre-trained biomedical language representation model for biomedical text mining. Bioinformatics, 36(4), 1234-1240. https://doi.org/10.1093/bioinformatics/btz682 [doi]
8. Isensee, F., Petersen, J., Klein, A., Zimmerer, D., Jaeger, P. F., Kohl, S., ... & Maier-Hein, K. H. (2018). nnu-net: Self-adapting framework for u-net-based medical image segmentation. arXiv preprint arXiv:1809.10486.

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http://echo.ismrm.org/p/ISMRM2026/368-02-002