Enhancing detection of various pancreatic lesions on endoscopic ultrasound through artificial intelligence: a basis for computer-aided detection systems.

Journal: Journal of gastroenterology and hepatology
PMID: 39538430

Abstract

BACKGROUND AND AIM: Endoscopic ultrasound (EUS) is the most sensitive method for evaluation of pancreatic lesions but is limited by significant operator dependency. Artificial intelligence (AI), in the form of computer-aided detection (CADe) systems, has shown potential in increasing accuracy and bridging operator dependency in several endoscopic domains. However, the complexity of integrating AI into EUS is far more challenging. This aims to develop and test the basis for a CADe system for real-time detection and segmentation of all pancreatic lesions.

Authors

  • Tom Konikoff
    Division of Gastroenterology, Rabin Medical Center, Petah Tikva, Israel; Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
  • Nadav Loebl
    Beilinson Medical Center Innovation, Artificial Intelligence Center, Rabin Medical Center, Petah Tikva, Israel, Faculty of Computer Science, Reichman University, Herzliya, Israel.
  • Ariel A Benson
    Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Institute of Gastroenterology and Liver Diseases, Jerusalem, Israel.
  • Orr Green
    Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv, Israel.
  • Hunter Sandler
    Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv, Israel.
  • Rachel Gingold-Belfer
    Division of Gastroenterology, Rabin Medical Center, Petach-Tikva, Israel.
  • Zohar Levi
    Division of Gastroenterology, Rabin Medical Center, Petach-Tikva, Israel.
  • Leor Perl
    Department of Cardiology, Rabin Medical Center, Petah Tikvah, Israel.
  • Iris Dotan
  • Steven Shamah
    Division of Gastroenterology, Rabin Medical Center, Petach-Tikva, Israel.

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