Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
331-02-015 / 331-02-015 ISMRM Abstract

Etiological Classification of White Matter Lesions Using Foundation Models: A Human-AI Collaboration Exploration

Primary: Analysis Methods - Classification and Prediction
Secondary: Neuro - White Matter
331-02-015 · AI Frontiers in Image Analysis · Monday, 11 May, 1:50 PM–3:06 PM · Roof Terrace
331-02-015 · AI Frontiers in Image Analysis · Monday, 11 May, 1:50 PM–3:06 PM · Roof Terrace
Keywords: White Matter Hyperintensities Diagnostic differentiation Foundation model Deep learning classification
Accepted
Shan Lv 1, Zebin Gao2,3, Yuerong Lizhu1, Ao Feng4, Cong Zhang5,6,7, Siyao Xu1, Tianyu Gao1, Feng Xu3,8, Yaou Liu1,9
1Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
2School of Information Science and Technology, Fudan University, Beijing, China
3Beijing National Research Center for Information Science and Technology,, Tsinghua University, Beijing, China
4Department of magnetic resonance imaging, Renmin Hospital, Hubei University of Medicine, Shiyan, Hubei Province, Shiyan, China
5Department of Neurology, Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, China
6Hebei Key Laboratory of Vascular Homeostasis and Hebei Collaborative Innovation Center for Cardio-Cerebrovascular Disease, Shijiazhuang, Hebei, China
7The Key Laboratory of Neurology (Hebei Medical University), Ministry of Education, Shijiazhuang, Hebei, China
8School of Software, Tsinghua University, Beijing, China
9China National Clinical Research Center for Neurological Diseases, Beijing, China
Presenting Author: Shan Lv

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References

1. Wolf NI, Engelen M, van der Knaap MS. MRI pattern recognition in white matter disease. Handb Clin Neurol 204:37–50 (2024). doi:10.1016/B978-0-323-99209-1.00019-3 [doi]
2. van der Knaap MS, Bugiani M. Leukodystrophies: a proposed classification system based on pathological changes and pathogenetic mechanisms. Acta Neuropathol 134:351–382 (2017). doi:10.1007/s00401-017-1739-1 [doi]
3. Hara K, Kataoka H, Satoh Y. Learning spatio-temporal features with 3D residual networks for action recognition. Proc IEEE Int Conf Comput Vis Workshop (ICCVW), Venice, Italy, pp. 3154–3160 (2017). doi:10.1109/ICCVW.2017.373 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/331-02-015