Artificial intelligence based surgical support for experimental laparoscopic Nissen fundoplication.

Journal: Frontiers in pediatrics
Published Date: May 23, 2025

Abstract

BACKGROUND: Computer vision (CV), a subset of artificial intelligence (AI), enables deep learning models to detect specific events within digital images or videos. Especially in medical imaging, AI/CV holds significant promise analyzing data from x-rays, CT scans, and MRIs. However, the application of AI/CV to support surgery has progressed more slowly. This study presents the development of the first image-based AI/CV model classifying quality indicators of laparoscopic Nissen fundoplication (LNF).

Authors

  • Holger Till
    Department of Pediatric and Adolescent Surgery, Medical University of Graz, Graz, Austria.
  • Ciro Esposito
    Pediatric Surgery Unit, Department of Translational Medical Science, Federico II University, 80131 Naples, Italy.
  • Chung Kwong Yeung
    Department of Surgery, University of Hong Kong, Hong Kong, China.
  • Dariusz Patkowski
    Department of Pediatric Surgery and Urology, Wroclaw Medical University, Wroclaw, Poland.
  • Sameh Shehata
    Department of Pediatric Surgery, University of Alexandria, Alexandria, Egypt.
  • Steve Rothenberg
    Department of Pediatric Surgery, Rocky Mountain Hospital for Children, Denver, CO, United States.
  • Georg Singer
    Department of Pediatric and Adolescent Surgery, Medical University of Graz, Graz, Austria.
  • Tristan Till
    Department of Applied Computer Sciences, FH JOANNEUM - University of Applied Sciences, Graz, Austria.

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