18F-FDG PET-based ensemble deep learning model for the prediction of lymphovascular invasion in colorectal cancer patients
The 2.5D ensemble DL model based on <sup>18</sup>F-FDG PET images performed well for the prediction of LVI in CRC, proving its potential as a precision medical support tool for CRC patients.
Authors
- Huiting Zhang (ORCID: https://orcid.org/0000-0002-5743-995X)
- Zhehao Lyu (ORCID: https://orcid.org/0009-0005-3160-2623)
- Yexin Su
- Peng Xu (ORCID: https://orcid.org/0000-0002-9830-5915)
- Ziyue Zhang (ORCID: https://orcid.org/0000-0002-6050-779X)
- Peng Fu (ORCID: https://orcid.org/0000-0002-9958-0150)
- Zhong‐Wei Lv (ORCID: https://orcid.org/0000-0003-2808-3357)
- Hongyue Zhao
Institutions
- Harbin Medical University (CN)
- Third Affiliated Hospital of Harbin Medical University (CN)
- Shanghai Public Health Clinical Center (CN)
- Shanghai Tenth People's Hospital (CN)
- First Affiliated Hospital of Harbin Medical University (CN)
Publication Details
- Journal
- Abdominal Radiology
- Published
- 2025-11-11
- DOI
- https://doi.org/10.1007/s00261-025-05282-3
- Primary Topic
- Medical Imaging Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00