Wireless capsule endoscopy multiclass classification using three-dimensional deep convolutional neural network model.

ABSTRACT:

Background

Wireless capsule endoscopy (WCE) is a patient-friendly and non-invasive technology that scans the whole of the gastrointestinal tract, including difficult-to-access regions like the small bowel. Major drawback of this technology is that the visual inspection of a large number of video frames produced during each examination makes the physician diagnosis process tedious and prone to error. Several computer-aided diagnosis (CAD) systems, such as deep network models, have been developed for the automatic recognition of abnormalities in WCE frames. Nevertheless, most of these studies have only focused on spatial information within individual WCE frames, missing the crucial temporal data within consecutive frames.

Methods

In this article, an automatic multiclass classi

SUBMITTER: Bordbar M 

PROVIDER: S-EPMC10722702 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature