Artificial intelligence and capsule endoscopy: automatic detection of enteric protruding lesions using a convolutional neural network.

Journal: Revista espanola de enfermedades digestivas
Published Date: Feb 1, 2023

Abstract

BACKGROUND AND AIMS: capsule endoscopy (CE) revolutionized the study of the small intestine. Nevertheless, reviewing CE images is time-consuming and prone to error. Artificial intelligence algorithms, particularly convolutional neural networks (CNN), are expected to overcome these drawbacks. Protruding lesions of the small intestine exhibit enormous morphological diversity in CE images. This study aimed to develop a CNN-based algorithm for the automatic detection small bowel protruding lesions.

Authors

  • Miguel Mascarenhas Saraiva
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • João Afonso
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Tiago Ribeiro
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • João Ferreira
    Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal.
  • Hélder Cardoso
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Patrícia Andrade
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Raquel Gonçalves
    Gastroenterology, Centro Hospitalar Universitário de São João.
  • Pedro Cardoso
    Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
  • Marco Parente
    Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal.
  • Renato Jorge
    Faculty of Engineering, Universidade do Porto.
  • Guilherme Macedo
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.

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