Automatic and Real‐Time Surgeon's Gazing Point Detection From Surgical Videos Using Machine Learning and Mathematical Algorithm
Our system successfully detected the surgeon's gaze point across procedures, suggesting potential utility in future AI-assisted surgery.
Authors
- Takeshi Takamoto
- Kenji Karako
- Ryo Oikawa (ORCID: https://orcid.org/0000-0003-0756-2164)
- Nobuhisa Akamatsu (ORCID: https://orcid.org/0000-0003-1603-5147)
- Shu Sasaki
- Morimasa Takayama (ORCID: https://orcid.org/0000-0001-5736-0064)
- Yuichiro Mihara (ORCID: https://orcid.org/0000-0001-5976-6041)
- Kiyoshi Hasegawa (ORCID: https://orcid.org/0000-0001-8734-740X)
- Yoshikuni Kawaguchi (ORCID: https://orcid.org/0000-0003-2986-3224)
- Kyoji Ito (ORCID: https://orcid.org/0000-0003-3913-1051)
Institutions
- National Center for Global Health and Medicine (JP)
- The University of Tokyo (JP)
Publication Details
- Journal
- Journal of Hepato-Biliary-Pancreatic Sciences
- Published
- 2025-12-19
- DOI
- https://doi.org/10.1002/jhbp.70052
- Primary Topic
- Gaze Tracking and Assistive Technology
- Type
- article
- Field-Weighted Citation Impact
- 0.00