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Endoscopic Procedures III: Video Capsule Endoscopy

Endoscopic Procedures III: Video Capsule Endoscopy

Capsule endoscopy, or wireless or video capsule endoscopy, is a diagnostic procedure for examining the entire gastrointestinal tract. Patients swallow a capsule about the size of a vitamin tablet. The capsule is equipped with a transmitter, a battery, an LED light source, and a color video camera to capture images throughout the gastrointestinal tract. This procedure is particularly useful for diagnosing conditions such as Crohn's disease, ulcerative colitis, tumors, polyps, ulcers,...

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Flexible Colonoscopy in Mice to Evaluate the Severity of Colitis and Colorectal Tumors Using a Validated Endoscopic Scoring System

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Computer-Aided Bleeding Detection Algorithms for Capsule Endoscopy: A Systematic Review.

Ahmmad Musha¹, Rehnuma Hasnat¹, Abdullah Al Mamun²

¹Department of Electrical and Electronic Engineering, Pabna University of Science and Technology, Pabna 6600, Bangladesh.

Sensors (Basel, Switzerland)

|August 26, 2023

Summary

This summary is machine-generated.

This systematic review analyzes computer-aided bleeding detection algorithms for capsule endoscopy (CE). It identifies key algorithms and their effectiveness for real-time gastrointestinal bleeding diagnosis.

Keywords:

bleeding classification bleeding detection bleeding recognition bleeding segmentation capsule endoscopy wireless capsule endoscopy

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Area of Science:

Medical Imaging
Gastroenterology
Artificial Intelligence

Background:

Capsule endoscopy (CE) generates extensive image data, making manual inspection for gastrointestinal bleeding diagnosis time-consuming.
Automated computer-aided bleeding detection systems are crucial for efficient real-time analysis of CE images.

Approach:

A systematic review was conducted using PRISMA methodology, searching five major repositories for relevant publications from 2001-2023.
147 full-text scientific papers were reviewed to identify and analyze state-of-the-art algorithms.

Key Points:

A taxonomy of computer-aided bleeding detection algorithms for CE is established.
Various algorithms utilizing different color spaces, feature extraction techniques, and classifiers are discussed.
The most effective algorithms for practical clinical application are identified.

Conclusions:

This review provides a comprehensive overview of current computer-aided bleeding detection techniques in CE.
Identified effective algorithms and future research directions aim to improve diagnostic accuracy and efficiency.