Identification of ulcers in wireless capsule endoscopy videos

Authors:
Alexandros Karargyris;Nikolaos Bourbakis
Affiliations:
College of Engineering, Assistive Technologies Research Center, Wright State University, Dayton, OH;College of Engineering, Assistive Technologies Research Center, Wright State University, Dayton, OH
Venue:
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Year:
2009

Citing 1
Cited 1

Detecting Abnormal Patterns in WCE Images

BIBE '05 Proceedings of the Fifth IEEE Symposium on Bioinformatics and Bioengineering

Ulcer detection in wireless capsule endoscopy video

Proceedings of the 20th ACM international conference on Multimedia

Quantified Score

Hi-index	0.00

Visualization

Abstract

Wireless Capsule Endoscopy (WCE) is a non invasive procedure which is used to view the lower gastrointestinal tract. Physicians can detect diseases such as bleeding, Crohn's disease, peptic ulcers, and colon cancer. In this paper a methodology is presented to identify peptic ulcers in the small intestine automatically. It first performs color transformation into the HSV color space; it utilizes log Gabor filters to find meaningful regions. A segmentation scheme is used to extract color information of these meaningful regions in the original RGB color space. Additionally, texture information is extracted and together with color values are fed into an artificial neural network for classification. Illustrative results from the methodology are also given in this paper.