Clearness of operating field: a surrogate for surgical skills on in vivo clinical data.

Journal: International journal of computer assisted radiology and surgery
Published Date:

Abstract

PURPOSE: Automatic surgical skill assessment is an emerging field beneficial to both efficiency and quality of surgical education and practice. Prior works largely evaluate skills on elementary tasks performed in the simulation laboratory, which cannot fully reflect the variety of intraoperative circumstances in the real operating room. In this paper, we attempt to fill this gap by expanding surgical skill assessment onto a clinical dataset including fifty-seven in vivo surgeries.

Authors

  • Daochang Liu
    Department of Computer Science, Peking University, Beijing, China.
  • Tingting Jiang
    Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, 06511, CT, USA.
  • Yizhou Wang
  • Rulin Miao
    Peking University Cancer Hospital, Beijing, China.
  • Fei Shan
    Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.
  • Ziyu Li
    Gastrointestinal Cancer Center, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital and Institute, Beijing, China.