Easy Scheme for Ulcer Detection in Wireless Capsule Endoscopy Images

Among the syndrome of many dangerous diseases in the human digestive tract ulcer is one of the most common. Diagnosis of small intestine ulcers cannot be detected by using other procedures of endoscopy. For visualizing these ulcers, wireless capsule endoscopy (WCE) technique is excessively being used. In WCE system a huge amount of images are achieved which is very much difficult and time erosive for physicians to check manually. So, for helping the physicians it is very much needed to provide an automated computer-aided system. In this paper, an automated computer-aided diagnosis system is mentioned for detecting ulcer from WCE images achieved from the capsule endoscopy video footage. In the first stage, we convert the source image into LAB color spaces for taking features. Then quadratic support vector machine (Q-SVM) classifier has been applied for separating the ulcer and non-ulcer images. Our achieved experiment results 90.39% accuracy and 99.00% sensitivity, validating the effectiveness of the proposed method. Therefore, results of the advanced methodology are given and statistical comparisons are also given related to the other works.