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

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Abstract

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.

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Notes

  1. www.capsuleendoscopy.org

  2. www.capsuleendoscopy.org

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Acknowledgments

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

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  1. LabSIV, Department of Computer Science, Faculty of Science, Ibn Zohr University, BP 8106, 80000, Agadir, Morocco

    Said Charfi & Mohamed El Ansari

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  1. Said Charfi
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  2. Mohamed El Ansari
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Correspondence to Said Charfi.

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Charfi, S., Ansari, M.E. Computer-aided diagnosis system for colon abnormalities detection in wireless capsule endoscopy images. Multimed Tools Appl 77, 4047–4064 (2018). https://doi.org/10.1007/s11042-017-4555-7

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