Quantitative measurements in capsule endoscopy

Comput Biol Med. 2015 Oct 1:65:333-47. doi: 10.1016/j.compbiomed.2015.07.016. Epub 2015 Jul 29.

Abstract

This review summarizes several approaches for quantitative measurement in capsule endoscopy. Video capsule endoscopy (VCE) typically provides wireless imaging of small bowel. Currently, a variety of quantitative measurements are implemented in commercially available hardware/software. The majority is proprietary and hence undisclosed algorithms. Measurement of amount of luminal contamination allows calculating scores from whole VCE studies. Other scores express the severity of small bowel lesions in Crohn׳s disease or the degree of villous atrophy in celiac disease. Image processing with numerous algorithms of textural and color feature extraction is further in the research focuses for automated image analysis. These tools aim to select single images with relevant lesions as blood, ulcers, polyps and tumors or to omit images showing only luminal contamination. Analysis of motility pattern, size measurement and determination of capsule localization are additional topics. Non-visual wireless capsules transmitting data acquired with specific sensors from the gastrointestinal (GI) tract are available for clinical routine. This includes pH measurement in the esophagus for the diagnosis of acid gastro-esophageal reflux. A wireless motility capsule provides GI motility analysis on the basis of pH, pressure, and temperature measurement. Electromagnetically tracking of another motility capsule allows visualization of motility. However, measurement of substances by GI capsules is of great interest but still at an early stage of development.

Keywords: Automated detection; Image analysis; Pressure; Scores; Video capsule endoscopy; Wireless motility capsule; pH.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Algorithms*
  • Capsule Endoscopy / methods*
  • Celiac Disease / pathology*
  • Crohn Disease / pathology*
  • Gastroesophageal Reflux / pathology*
  • Humans
  • Image Processing, Computer-Assisted / methods*