Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
468-03-009 ISMRM Abstract

Robust Cross-Center Vessel Lumen and Wall Segmentation on Intracranial Vessel Wall MRI via Anatomy-Aware Learning

Primary: Cardiovascular - Vascular and Vessel Wall
Secondary: Analysis Methods - Segmentation and Detection
468-03-009 · Segmentation for Cardiac Applications · Tuesday, 12 May, 1:40 PM–2:35 PM · Digital Posters Row I
Keywords: Unsupervised learning Single-source Domain Generalization Automated intracranial vessel segmentation Deep learning interpretability
Accepted
Xin Wang1, Gador Canton2, Zhiwei Tan1, Yin Guo3, Dan Cheng2,4, Mona Kharaji2, Beibei Sun2, Jie Sun2, Duygu B Geleri2, David L Tirschwell5, Thomas S Hatsukami6, Mahmud Mossa-Basha2,4, Niranjan Balu 2, Chun Yuan2
1Department of Electrical and Computer Engineering, University of Washington, Seattle, United States of America
2Department of Radiology, University of Washington, Seattle, United States of America
3Department of Bioengineering, University of Washington, Seattle, United States of America
4Department of Radiology, University of Alabama at Birmingham, Birmingham, United States of America
5Department of Neurology, University of Washington, Seattle, United States of America
6Department of Surgery, University of Washington, Seattle, United States of America
Presenting Author: Niranjan Balu

Synopsis

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References

1. Guo, Y. et al. (2024), Plaque Evolution and Vessel Wall Remodeling of Intracranial Arteries: A Prospective, Longitudinal Vessel Wall MRI Study. J Magn Reson Imaging, 60: 889-899. https://doi.org/10.1002/jmri.29185 [doi]
2. Yu, A.C., Mohajer, B., and Eng, J. (2022). External Validation of Deep Learning Algorithms for Radiologic Diagnosis: A Systematic Review. Radiology: Artificial Intelligence, 4(3), e210064. https://doi.org/10.1148/ryai.210064 [doi]
3. Wang, X. et al. (2026). RemInD: Remembering Anatomical Variations for Interpretable Domain Adaptive Medical Image Segmentation. In: Oguz, I., Zhang, S., Metaxas, D.N. (eds) Information Processing in Medical Imaging. IPMI 2025. Lecture Notes in Computer Science, vol 15829. Springer, Cham. https://doi.org/10.1007/978-3-031-96628-6_22 [doi]
4. Wang, X. et al. (2025). Unified and Semantically Grounded Domain Adaptation for Medical Image Segmentation. arXiv preprint arXiv:2508.08660. https://arxiv.org/abs/2508.08660
5. Chen, L. et al. (2018), Development of a quantitative intracranial vascular features extraction tool on 3D MRA using semiautomated open-curve active contour vessel tracing. Magn. Reson. Med, 79: 3229-3238. https://doi.org/10.1002/mrm.26961 [doi]
6. Guo, Y. et al. (2022), Multi-Planar, Multi-Contrast and Multi-Time Point Analysis Tool (MOCHA) for Intracranial Vessel Wall Characterization. J Magn Reson Imaging, 56: 944-955. https://doi.org/10.1002/jmri.28087 [doi]
7. Oktay, O. et al. (2018). Attention U-Net: Learning Where to Look for the Pancreas. 10.48550/arXiv.1804.03999. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/468-03-009