An integrative deep learning model based on dual-mode ultrasound for diagnosing gallbladder polyps
Diagnosing gallbladder polyps through a deep learning model based on conventional ultrasound presents challenges. IDL model enables automated segmentation of the gallbladder and diagnosis of gallbladder polyps. The IDL model is a reliable tool to assist junior radiologists in diagnosis and has potential for reducing unnecessary cholecystectomies.
Authors
- Haixia Yuan
- Zhidan Geng (ORCID: https://orcid.org/0009-0000-3831-6834)
- YU Qing
- YiLei Shi
- Xiao Xiang Zhu
- Congyu Tang
- Lifan Wang
- Xing Zhao
- Chunlei Li
- Peishan Guan
- Wenping Wang
- Jianfei Chen
Institutions
- Fudan University (CN)
- Shanghai University of Traditional Chinese Medicine (CN)
- Zhongshan Hospital of Xiamen University (CN)
- Zhongshan Hospital (CN)
- Shanghai Traditional Chinese Medicine Hospital (CN)
- Technical University of Munich (DE)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2026-02-02
- DOI
- https://doi.org/10.1186/s13244-026-02213-8
- Primary Topic
- Cholangiocarcinoma and Gallbladder Cancer Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Fujian Province