Multimedia Tools and Applications

, Volume 77, Issue 3, pp 4047–4064 | Cite as

Computer-aided diagnosis system for colon abnormalities detection in wireless capsule endoscopy images



Wireless capsule endoscopy (WCE) is a novel imaging technique that can travel through human body and image the small bowel entirely. Therefore, it has been gradually adopted compared with traditional endoscopies for gastrointestinal diseases. However, the big number of the produced images by a WCE test makes their review exhaustive for the physicians. It is helpful for clinicians if we can develop a computer-aided diagnosis system for the task of identifying the images with potential problems. The aim of this paper is to automatize the process of WCE images abnormalities detection by presenting a new texture extraction scheme for pathological inflammation, polyp, and bleeding regions discrimination in WCE images. A new approach based on local binary pattern variance and discrete wavelet transform is proposed. The new textural features scheme has many advantages, e.g., it detects multi-directional characteristics and overcomes the illuminations changes in WCE images. Intensive experiments are conducted on two datasets constructed from several WCE exams. The promising results make the presented method suitable for abnormalities detection in WCE images.


Wireless capsule endoscopy Gastrointestinal tract Discrete wavelet transform (DWT) Local binary pattern (LBP) LBP variance 



We gratefully acknowledge and express our thanks to the National Center for Scientific and technical Research (CNRST) in Rabat for its research grant.

Compliance with Ethical Standards

Conflict of interests

The authors declare that they have no conflict of interest.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.LabSIV, Department of Computer Science, Faculty of ScienceIbn Zohr UniversityAgadirMorocco

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