Robust lumen segmentation based on temporal residual U-Net using spatiotemporal features in intravascular optical coherence tomography images
TR-Unet establishes a robust and effective spatiotemporal fusion paradigm for IVOCT segmentation, demonstrating significant robustness to artifacts and providing architectural insights for temporal modeling optimization.
Authors
- Mingrui He (ORCID: https://orcid.org/0000-0002-3324-2511)
- Junfeng Jiang (ORCID: https://orcid.org/0000-0003-0393-8451)
- Yuankang Wang
- Tiegen Liu (ORCID: https://orcid.org/0000-0003-4141-6961)
- Qingrui Li (ORCID: https://orcid.org/0000-0001-9711-4239)
- Zhenyang Ding (ORCID: https://orcid.org/0000-0002-0483-477X)
- Kun Liu (ORCID: https://orcid.org/0000-0003-2460-6851)
- Shanshan Zhou (ORCID: https://orcid.org/0000-0003-1689-0266)
- Yin Yu
- Rongyang Zhu
- Hao Kuang (ORCID: https://orcid.org/0009-0008-0807-1846)
Institutions
- Tianjin University (CN)
- Chinese PLA General Hospital (CN)
- Tianjin International Joint Academy of Biomedicine (CN)
Publication Details
- Journal
- Journal of Biomedical Optics
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1117/1.jbo.30.10.106003
- Primary Topic
- Optical Coherence Tomography Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00