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

Endosc Int Open 2021; 09: E1264-E1268 DOI: 10.1055/a-1490-8960Colon 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. [...] Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, GermanyArticle in Thieme eJournals: Table of contents  |  Abstract  |  open access Full text
Source: Endoscopy International Open - Category: Gastroenterology Authors: Tags: Innovation forum Source Type: research