A Novel Real-time Automatic Angioectasia Detection Method in Wireless Capsule Endoscopy Video Feed.

Abstract

The development of Wireless Capsule Endoscopy (WCE) revolutionized the examination of the small bowel for diseases. Upon swallowing a capsule (a microscopic camera that resembles an ordinary pill in both shape and size), images of the patient's gastrointestinal (GI) tract are wirelessly transmitted from it to an external recorder. The inspection of these images is, to this day, still manually performed by medical professionals - a lengthy, and especially prone to errors, process. One of the most common diagnoses is the presence of angioectasias, i.e. ectatic vessels on the GI tract that are predisposed to bleeding. In this paper, a novel method for automatic detection of these lesions is proposed, using a combination of low-level image processing, feature detection and machine learning, that can run in real-time without the need for specialized hardware or graphics cards, achieving 92.7% sensitivity and 99.5% specificity to angioectasias. This method can also be expanded to include more pathologies.