3D auto-segmentation of pancreas cancer and surrounding anatomical structures for surgical planning
The deep learning-based autosegmentation model for 3D visualization of pancreatic cancer and peripancreatic structures showed robust performance. Further improvement will enhance many promising applications in clinical research.
Authors
- Woo Kyoung Jeong (ORCID: https://orcid.org/0000-0002-0676-2116)
- Namkee Oh (ORCID: https://orcid.org/0000-0002-6594-8973)
- Jinsoo Rhu (ORCID: https://orcid.org/0000-0001-9809-8525)
- Ji Hye Min (ORCID: https://orcid.org/0000-0002-8496-6771)
- Ji Eun Lee (ORCID: https://orcid.org/0000-0002-4442-4441)
- Jong Man Kim (ORCID: https://orcid.org/0000-0002-1903-8354)
- Jisun Lee (ORCID: https://orcid.org/0000-0002-6264-7171)
- Gyu-Seong Choi
- Seo-Youn Choi
Institutions
- GTx (United States) (US)
- Soonchunhyang University (KR)
- Samsung Medical Center (KR)
- Chungbuk National University Hospital (KR)
- Bucheon University (KR)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- International Journal of Surgery
- Published
- 2025-06-27
- DOI
- https://doi.org/10.1097/js9.0000000000002835
- Citations
- 3
- Primary Topic
- Pancreatic and Hepatic Oncology Research
- Type
- article
- Field-Weighted Citation Impact
- 3.14