An observational study in Cholecystectomy and Surgical Video Identification, sponsored by Chinese Academy of Sciences. Recruiting at 5 sites in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-09-05.
Sponsored by Chinese Academy of Sciences · Observational
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.
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.
Chinese Academy of Sciences is the lead sponsor of 65 studies on the registry; 13 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Patients aged 18 or above who are diagnosed by a doctor as needing laparoscopic cholecystectomy
Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.
Exclusion Criteria:
patients aged 18 years and older 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.
Diagnostic Test: AI-assisted Intraoperative Anatomy Analysis
patients aged 18 years and older 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.
Diagnostic Test: AI-assisted Intraoperative Anatomy Analysis
patients aged 18 years and older 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.
Diagnostic Test: AI-assisted Intraoperative Anatomy Analysis
patients aged 18 years and older 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
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.
Dice Similarity Coefficient
Dice Similarity Coefficient is a statistical measure of the similarity between two sets of data. In the context of image segmentation, it is used to quantify the spatial overlap between a predicted segmentation mask and its corresponding ground truth mask.
Time frame: 3 years
Mean Intersection over Union
Mean Intersection over Union provides a measure of the overlap between the predicted segmentation and the ground truth, averaged across all classes present in the dataset.
Time frame: 3 years
Global Accuracy
The proportion of correctly classified pixels out of the total number of pixels in the image.
Time frame: 3 years
Inference Latency
time taken by the algorithm to process a single video frame and generate the segmentation masks (inference latency), or equivalently, the number of frames processed per second
Time frame: 3 years
Class-Specific Precision and Recall for Critical Structures
Precision: The proportion of predicted pixels for a structure that are actually part of that structure Recall: The proportion of actual ground truth pixels for a structure that were correctly identified by the algorithm
Time frame: 3 years
Plan to share: Undecided
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Chinese Academy of Sciences