Convenient Way to Detect Ulcer in Wireless Capsule Endoscopy Through Fuzzy Logic Technique

The ulcer is one of the most common and dangerous among the effect of many deadly diseases in the Gastrointestinal tract. It is complicated to diagnose and detect the tiny intestine ulcers by applying other alternative methods of endoscopy. Wireless Capsule Endoscopy (WCE) technique is rapidly using more conveniently to visualize these ulcers. However, it is challenging and time-consuming for the clinicians to check the vast amount of images captured from the WCE. So, it has become the most crucial concern to provide an automated system for detecting the ulcer to help the clinicians. In this research paper, a unique automatic ulcer diagnosis model is introduced to detect ulcers from images that have been converted from the captured WCE video. In the proposed method, Some consecutive approaches, like pre-processing and fuzzy logic framework, have been applied for extracting the ulcer portion on L*a*b colour model. The proposed method has obtained a tremendous result of sensitivity 95%, accuracy 95.5%, specificity 97%, F1 score 96.48%, precision 98%, and negative predicted value 91% by utilizing the statistical feature and KNN classifier. Therefore, from the analysis of the analytical results and comparison studies, it is highly optimistic about having a positive impact on this research arena.