Automatic segmentation and reconstruction of lower-extremity arteries from computed tomography angiography images via a deep learning framework
The LEAS-Net can be used as an AI tool to reconstruct lower-extremity arteries from CTA images for planning perforator flap transplantation.
Authors
- Lulu Tan (ORCID: https://orcid.org/0009-0005-2212-6485)
- Huijun Hu (ORCID: https://orcid.org/0000-0003-1086-4788)
- Zehong Yang (ORCID: https://orcid.org/0000-0001-7562-3710)
- Guoxiong Lu
- Jun Shen (ORCID: https://orcid.org/0000-0003-3014-8463)
- Yusong Jiang (ORCID: https://orcid.org/0000-0001-7194-4445)
- Xiang Liu (ORCID: https://orcid.org/0000-0001-7682-6886)
Institutions
- Sun Yat-sen University (CN)
- Sun Yat-sen Memorial Hospital (CN)
- United Imaging Healthcare (China) (CN)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-10-29
- DOI
- https://doi.org/10.21037/qims-2025-1051
- Primary Topic
- Reconstructive Surgery and Microvascular Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00