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Computer vision in surgery: from potential to clinical value.

Pietro Mascagni1,2,3, Deepak Alapatt4, Luca Sestini4,5

  • 1Gemelli Hospital, Catholic University of the Sacred Heart, Rome, Italy. pietro.mascagni@ihu-strasbourg.eu.

NPJ Digital Medicine
|October 28, 2022
PubMed
Summary
This summary is machine-generated.

Computer vision (CV) enhances minimally invasive surgery by analyzing surgical video data. Despite its potential for improving decision-making and safety, widespread clinical adoption of CV tools in surgery remains limited.

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Area of Science:

  • Surgical Technology
  • Medical Imaging
  • Computer Science

Background:

  • Minimally invasive surgery utilizes fiber optic cameras and robots, generating vast amounts of visual data.
  • Computer vision (CV) analyzes visual data to interpret surgical procedures, aiming to aid surgeons.
  • Current applications of CV in surgery are limited, with no widely adopted diagnostic or therapeutic tools.

Purpose of the Study:

  • To review current computer vision techniques applied to minimally invasive surgery.
  • To examine the clinical applications of these CV techniques.
  • To identify challenges hindering the broader implementation of CV in surgical practice.

Main Methods:

  • Literature review of computer vision applications in minimally invasive surgery.
  • Case study focusing on laparoscopic cholecystectomy.
  • Analysis of current CV techniques and their clinical relevance.

Main Results:

  • Various CV techniques have been explored for applications in minimally invasive surgery.
  • Specific examples of CV applications were identified, particularly in laparoscopic cholecystectomy.
  • Significant challenges impede the widespread adoption and clinical integration of CV tools.

Conclusions:

  • CV holds substantial promise for augmenting surgical decision-making, enhancing safety, and expanding access to care.
  • Overcoming technical, regulatory, and integration hurdles is crucial for realizing the full potential of CV in surgery.
  • Further research and development are needed to bridge the gap between CV capabilities and routine clinical use.