A deep learning detection method for pancreatic cystic neoplasm based on Mamba architecture
M-YOLO(Mamba YOLOv10) enhances the identification performance of PCN by integrating the deep feature extraction capability of Mamba and the fast localization technique of YOLOv10.
Authors
- Yun Bian (ORCID: https://orcid.org/0000-0002-4863-4956)
- Liang Jin (ORCID: https://orcid.org/0000-0002-7552-7849)
- Jie Wu (ORCID: https://orcid.org/0000-0002-7211-2816)
- Chengwei Chen (ORCID: https://orcid.org/0000-0001-6293-5387)
- Cong He (ORCID: https://orcid.org/0000-0002-7231-8224)
- J. P. Dai (ORCID: https://orcid.org/0000-0003-4802-4485)
Institutions
- University of Shanghai for Science and Technology (CN)
- Second Military Medical University (CN)
- Fudan University (CN)
- Huadong Hospital (CN)
Publication Details
- Journal
- Journal of X-Ray Science and Technology
- Published
- 2025-02-18
- DOI
- https://doi.org/10.1177/08953996251313719
- Citations
- 1
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 1.05
Funders
- Science and Technology Innovation Plan Of Shanghai Science and Technology Commission