Segmentation of WCE Images Using Fuzzy Active Contour Method

Nowadays bowel tumor becomes an eminent issue in grasping the attention of both the medical and scientific fields because of the hindrance in treating the disease. Wireless capsule endoscopy assists in diagnosing GI conditions in the small bowel. In this method an average of nearly 50, 000 images are taken. Scrutinizing and evaluating all those recorded images is tedious and time consuming. Hence we go for computerized approaches in order to deteriorate the physicians burden. In this paper a fuzzy active contour based image segmentation method is proposed and its result is analogized with other methods like Adaptive Thresholding (AT), Edge detecting and Region Growing by Adaptive threshold (RGA) in terms of parameters like Energy, Relative Entropy (RE) and Elapsed time (ET). The experimental results validate that our model works efficiently.