Deep Learning and Minimally Invasive Endoscopy: Automatic Classification of Pleomorphic Gastric Lesions in Capsule Endoscopy.

Journal: Clinical and translational gastroenterology
Published Date: Oct 1, 2023

Abstract

INTRODUCTION: Capsule endoscopy (CE) is a minimally invasive examination for evaluating the gastrointestinal tract. However, its diagnostic yield for detecting gastric lesions is suboptimal. Convolutional neural networks (CNNs) are artificial intelligence models with great performance for image analysis. Nonetheless, their role in gastric evaluation by wireless CE (WCE) has not been explored.

Authors

  • Miguel Mascarenhas
    Precision Medicine Unit, Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
  • Francisco Mendes
    Precision Medicine Unit, Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
  • Tiago Ribeiro
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • João Afonso
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Pedro Cardoso
    Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
  • Miguel Martins
    Precision Medicine Unit, Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, 4200-427 Porto, Portugal.
  • Hélder Cardoso
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Patrícia Andrade
    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.
  • Miguel Mascarenhas Saraiva
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.
  • Guilherme Macedo
    Department of Gastroenterology, São João University Hospital, Porto, Portugal.

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