Open AccessRecognition of esophagitis in endoscopic images using transfer learning
Author(s) -
Elena Caires Silveira,
Caio Fellipe Santos Corrêa,
Leonardo Madureira Silva,
Bruna Almeida Santos,
Soraya Mattos Pretti,
Fabrício Freire de Melo
Publication year - 2022
Publication title -
world journal of gastrointestinal endoscopy
Language(s) - English
Resource type - Journals
ISSN - 1948-5190
DOI - 10.4253/wjge.v14.i5.311
Subject(s) - artificial intelligence , convolutional neural network , pattern recognition (psychology) , test set , deep learning , transfer of learning , computer science , binary classification , esophagitis , medicine , support vector machine , disease , reflux
Esophagitis is an inflammatory and damaging process of the esophageal mucosa, which is confirmed by endoscopic visualization and may, in extreme cases, result in stenosis, fistulization and esophageal perforation. The use of deep learning (a field of artificial intelligence) techniques can be considered to determine the presence of esophageal lesions compatible with esophagitis.