Computer vision augmented indocyanine green near-infrared fluorescence (ICG-NIRF) signal-to-background ratio (SBR) for identification of extrahepatic biliary structures in laparoscopic cholecystectomy - Summary - MDSpire
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Computer vision–enhanced signal-to-background analysis of indocyanine green near-infrared fluorescence to identify extrahepatic biliary anatomy during laparoscopic cholecystectomy
To assess whether computer vision can improve the signal-to-background ratio (SBR) of indocyanine green near-infrared fluorescence (ICG-NIRF) for identifying extrahepatic biliary ducts during laparoscopic cholecystectomy, and to demonstrate feasibility of combining ICG-NIRF with white-light imaging.
Approach:
Study rationale: The authors hypothesized that attenuating background liver fluorescence would improve detection of biliary structures and explored a multimodal computer-vision method to highlight ducts while retaining white-light anatomical context.
Video dataset: A multi-institutional database contained 928 adult and pediatric laparoscopic cholecystectomy videos collected from January 2019 through March 2025. ICG-NIRF was used in 156 cases.
Frame selection: Eligible videos showed the gallbladder and extrahepatic ducts with biliary fluorescence and minimal blur or camera instability. Screening yielded 487 clips; frames were extracted at two per second.
Key Findings:
The supplied context describes the study rationale and initial data-processing methods but does not provide quantitative results.
The authors propose a computer-vision fusion image that selectively enhances extrahepatic ducts in ICG-NIRF while preserving surrounding white-light anatomy.
Interpretation:
The study is designed to address background fluorescence and subjective interpretation that can limit ICG-NIRF visualization. The provided context establishes the hypothesis and technical aim, but does not report whether the method improved SBR or clinical outcomes.
Limitations:
The supplied article context ends during the methods section and does not include the full methods, results, or discussion.
No quantitative performance measures, validation details, or clinical outcome data are provided in the supplied context.
Conclusion:
The authors describe a computer-vision approach intended to improve ICG-NIRF biliary visualization and combine it with white-light anatomical context; its effectiveness cannot be determined from the provided material.
by Philip J. Seger, Shinil Shah, Akhil Gorugantu, Nan Xi, Brendan T. Fox, Rishikesh Bhyri, Kaity Tung, Rita Glazer, Brian Quaranto, Junsong Yuan, Erik Wilson, Gene Yang, Steven D. Schwaitzberg, Peter C. W. Kim