Tundra Space

Tundra Space

Clinical Research Directory

Browse clinical research sites, groups, and studies.

Back to Studies
RECRUITING
NCT07158372

Research on Identifying Critical Surgical Anatomy in Cholecystectomy Videos Based on Deep Learning

Sponsor: Chinese Academy of Sciences

View on ClinicalTrials.gov

Summary

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.

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

200

Start Date

2025-08-15

Completion Date

2028-08-15

Last Updated

2025-09-05

Healthy Volunteers

No

Interventions

DIAGNOSTIC_TEST

AI-assisted Intraoperative Anatomy Analysis

This is a prospective study on patients aged 18 years or more diagnosed with laparoscopic cholecystectomy. We will collect information such as laparoscopic cholecystectomy videos and procedure type, excluding patients who did not undergo surgery at the original hospital or whose videos were blurry.

Locations (5)

The First Affiliated Hospital of Zhengzhou University

Zhengzhou, Henan, China

Beijing Anzhen Hospital, Capital Medical University

Beijing, China

Beijing Luhe Hospital, Capital Medical University

Beijing, China

Peking university people's hospital

Beijing, China

Shanghai East Hospital of Tongji University

Shanghai, China