CC BY-NC-ND 4.0 · Endosc Int Open 2021; 09(08): E1264-E1268
DOI: 10.1055/a-1490-8960
Innovation forum

Artificial intelligence and colon capsule endoscopy: automatic detection of blood in colon capsule endoscopy using a convolutional neural network

Miguel Mascarenhas Saraiva
1  Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, Porto, Portugal
3  Faculty of Medicine of the University of Porto, Alameda Professor Hernâni Monteiro, Porto, Portugal
,
João P. S. Ferreira
4  Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal
5  INEGI – Institute of Science and Innovation in Mechanical and Industrial Engineering, Porto, Portugal
,
Hélder Cardoso
1  Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, Porto, Portugal
3  Faculty of Medicine of the University of Porto, Alameda Professor Hernâni Monteiro, Porto, Portugal
,
João Afonso
1  Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, Porto, Portugal
2  WGO Gastroenterology and Hepatology Training Center, Porto, Portugal
,
Tiago Ribeiro
1  Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, Porto, Portugal
2  WGO Gastroenterology and Hepatology Training Center, Porto, Portugal
,
Patrícia Andrade
1  Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, Porto, Portugal
3  Faculty of Medicine of the University of Porto, Alameda Professor Hernâni Monteiro, Porto, Portugal
,
Marco P. L. Parente
4  Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal
5  INEGI – Institute of Science and Innovation in Mechanical and Industrial Engineering, Porto, Portugal
,
Renato N. Jorge
4  Department of Mechanical Engineering, Faculty of Engineering of the University of Porto, Porto, Portugal
5  INEGI – Institute of Science and Innovation in Mechanical and Industrial Engineering, Porto, Portugal
,
Guilherme Macedo
1  Department of Gastroenterology, São João University Hospital, Alameda Professor Hernâni Monteiro, Porto, Portugal
3  Faculty of Medicine of the University of Porto, Alameda Professor Hernâni Monteiro, Porto, Portugal
› Author Affiliations

Abstract

Colon capsule endoscopy (CCE) is a minimally invasive alternative to conventional colonoscopy. Most studies on CCE focus on colorectal neoplasia detection. The development of automated tools may address some of the limitations of this diagnostic tool and widen its indications for different clinical settings. We developed an artificial intelligence model based on a convolutional neural network (CNN) for the automatic detection of blood content in CCE images. Training and validation datasets were constructed for the development and testing of the CNN. The CNN detected blood with a sensitivity, specificity, and positive and negative predictive values of 99.8 %, 93.2 %, 93.8 %, and 99.8 %, respectively. The area under the receiver operating characteristic curve for blood detection was 1.00. We developed a deep learning algorithm capable of accurately detecting blood or hematic residues within the lumen of the colon based on colon CCE images.



Publication History

Received: 12 January 2021

Accepted: 12 March 2021

Publication Date:
16 July 2021 (online)

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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