Real‐Time Guidewire Tip Tracking Using a Siamese Network for Image‐Guided Endovascular Procedures
Siamese Network This paper proposed a novel AI framework that enhances guidewire tip tracking in image-guided therapy for vascular diseases. Combining a Siamese network with attention mechanisms ensures robust tracking despite visual ambiguities and tissue deformations. Validated on clinical angiography sequences and robotic platforms, it improves diagnostic and therapeutic precision in endovascular interventions. More details can be found in the Research Article by Peng Qi and co-workers (DOI: 10.1002/aisy.202500425).
Authors
- Peng Qi (ORCID: https://orcid.org/0000-0003-0514-9464)
- Tianliang Yao (ORCID: https://orcid.org/0009-0000-7063-3880)
- Yixuan Yuan (ORCID: https://orcid.org/0000-0002-0853-6948)
- Yong Li (ORCID: https://orcid.org/0000-0002-2999-8164)
- Zhiqiang Pei
Institutions
- Tongji University (CN)
- University of Shanghai for Science and Technology (CN)
- Chinese University of Hong Kong (HK)
- Shanghai Technical Institute of Electronics & Information (CN)
- Shanghai East Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- Advanced Intelligent Systems
- Published
- 2025-10-01
- DOI
- https://doi.org/10.1002/aisy.70133
- Citations
- 1
- Primary Topic
- Digital Imaging in Medicine
- Type
- article
- Field-Weighted Citation Impact
- 1.88