Computer-aided anatomy recognition in intrathoracic and -abdominal surgery: a systematic review.

Journal: Surgical endoscopy
Published Date: Aug 4, 2022

Abstract

BACKGROUND: Minimally invasive surgery is complex and associated with substantial learning curves. Computer-aided anatomy recognition, such as artificial intelligence-based algorithms, may improve anatomical orientation, prevent tissue injury, and improve learning curves. The study objective was to provide a comprehensive overview of current literature on the accuracy of anatomy recognition algorithms in intrathoracic and -abdominal surgery.

Authors

  • R B den Boer
    Department of Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
  • C de Jongh
    Department of Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
  • W T E Huijbers
    Department of Surgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
  • T J M Jaspers
    Department of Biomedical Engineering, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, The Netherlands.
  • J P W Pluim
    Medical Image Analysis Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • R van Hillegersberg
    Department of Surgery, University Medical Center Utrecht, Utrecht, The Netherlands. r.vanhillegersberg@umcutrecht.nl.
  • M Van Eijnatten
    Department of Biomedical Engineering, Eindhoven University of Technology, Groene Loper 3, 5612 AE, Eindhoven, The Netherlands.
  • J P Ruurda
    Department of Surgery, University Medical Center Utrecht, Utrecht, The Netherlands.

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