Research on Identifying Critical Surgical Anatomy in Cholecystectomy Videos Based on Deep Learning
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorChinese Academy of Sciences
About this trial
Laparoscopic cholecystectomy is a common surgical procedure, but it carries the potential for bile duct injury and other surgical risks. To provide visual assistance to surgeons during surgery and mitigate these risks, this research project aims to develop a real-time object recognition algorithm based on deep learning technology. This algorithm will label key anatomical structures in laparoscopic cholecystectomy videos, providing surgeons with immediate information on dangerous and safe areas.
Eligibility criteria
Qualifiers
Patients aged 18 or above who are diagnosed by a doctor as needing laparoscopic cholecystectomy
Disqualifiers
Patients who did not undergo surgery at the original hospital and those whose videos were blurry were excluded.
Trial design
Treatments tested in this trial
- AI-assisted Intraoperative Anatomy Analysis
Treatment groups
200 Participants
are divided into 4 treatment groupsSponsors and collaborators
Chinese Academy of Sciences
Lead sponsor
The First Affiliated Hospital of Zhengzhou University
Collaborator
Capital Medical University
Collaborator
Beijing Anzhen Hospital
Collaborator
Shanghai East Hospital of Tongji University
Collaborator
Peking University People's Hospital
Collaborator
Source ClinicalTrials.gov