Detection of abnormalities in wireless capsule endoscopy based on extreme learning machine
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ORIGINAL PAPER
Detection of abnormalities in wireless capsule endoscopy based on extreme learning machine Ayoub Ellahyani1
· Ilyas El Jaafari1 · Said Charfi2 · Mohamed El Ansari2
Received: 28 June 2020 / Revised: 26 September 2020 / Accepted: 26 October 2020 © Springer-Verlag London Ltd., part of Springer Nature 2020
Abstract Wireless capsule endoscopy (WCE) is a device that can move through human body and capture the small bowel entirely. Thus, it is presented as an excellent diagnostic tool for evaluation of gastrointestinal diseases compared with traditional endoscopies. However, the diagnosis by the physicians is tedious since it requires reviewing the video extracted from the capsule and analysing all of its frames. This tedious task has fuelled the efforts of researchers to provide automated diagnostic techniques for WCE frameworks to detect symptoms of gastrointestinal illness. In this paper, a new computer-aided diagnosis method for abnormalities detection in WCE images is proposed. After a preprocessing step, we extract from these images the descriptor we feed to a kernel extreme learning machine to perform the classification process. The descriptor used in this work is a combination between the histogram of oriented gradients (HOG) that were extracted using the hue component of the HSV colour space, and a modified rotation-invariant local binary pattern. The proposed approach has been tested on different datasets, and the results obtained are satisfactory when compared to the state-of-the-art works. Keywords Wireless capsule endoscopy · Computer-aided detection · Feature extraction · Extreme learning machine
1 Introduction Diseases of the digestive tract, such as oesophagus, stomach and small intestine, colon and other digestive organs cancers pose a serious threat to human health. Many types of endoscopy are employed to examine the patient’s gastrointestinal tract. For example, gastro-copy, pressure enteroscopy and colonoscopy are used to examine the human digestive system. However, most of the above endoscopy tests are limited to examine the human small intestine. To overcome these
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Ayoub Ellahyani [email protected] Ilyas El Jaafari [email protected] Said Charfi [email protected] Mohamed El Ansari [email protected]
1
LabSIE, Department of Mathematics and Computer Science, Multidisciplinary Faculty, Ibn Zohr University, BP 638, 45000 Ouarzazate, Morocco
2
LabSIV, Department of Computer Science, Faculty of Science, Ibn Zohr University, BP 8106, 80000 Agadir, Morocco
limitations, the WCE examination developed by Given Imaging in 2000 was presented as an excellent diagnostic tool for evaluation of gastrointestinal bleeding, ulcers, Crohn’s disease and other digestive abnormalities [22]. Nevertheless, the review or analysis of these videos by physicians can take several hours, which is tiring, so they may miss parts where abnormalities of the gastrointestinal tract are present, since these parts are often present only in a few frames of the video sequence. Furthermore, the size
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