Wireless capsule endoscopy color video segmentation

Mackiewicz, Michal ORCID: https://orcid.org/0000-0002-8777-8880, Berens, Jeff and Fisher, Mark (2008) Wireless capsule endoscopy color video segmentation. IEEE Transactions on Medical Imaging, 27 (12). pp. 1769-1781. ISSN 0278-0062

Full text not available from this repository. (Request a copy)


This paper describes the use of color image analysis to automatically discriminate between oesophagus, stomach, small intestine, and colon tissue in wireless capsule endoscopy (WCE). WCE uses ldquopill-camrdquo technology to recover color video imagery from the entire gastrointestinal tract. Accurately reviewing and reporting this data is a vital part of the examination, but it is tedious and time consuming. Automatic image analysis tools play an important role in supporting the clinician and speeding up this process. Our approach first divides the WCE image into subimages and rejects all subimages in which tissue is not clearly visible. We then create a feature vector combining color, texture, and motion information of the entire image and valid subimages. Color features are derived from hue saturation histograms, compressed using a hybrid transform, incorporating the discrete cosine transform and principal component analysis. A second feature combining color and texture information is derived using local binary patterns. The video is segmented into meaningful parts using support vector or multivariate Gaussian classifiers built within the framework of a hidden Markov model. We present experimental results that demonstrate the effectiveness of this method.

Item Type: Article
Faculty \ School: Faculty of Science > School of Computing Sciences
UEA Research Groups: Faculty of Science > Research Groups > Interactive Graphics and Audio
Faculty of Science > Research Groups > Colour and Imaging Lab
Depositing User: Vishal Gautam
Date Deposited: 07 Mar 2011 13:34
Last Modified: 27 Oct 2023 00:37
URI: https://ueaeprints.uea.ac.uk/id/eprint/21637
DOI: 10.1109/TMI.2008.926061

Actions (login required)

View Item View Item