Detection of uninformative regions in wireless capsule endoscopy images
Wireless capsule endoscopy (WCE) is able to investigate the entire gastrointestinal tract including the small bowel. To reduce the reviewing time of captured images by gastroenterologists and increasing the accuracy rate for automatic detection of abnormalities, it is beneficial to remove regions which have less or no clinical information of small bowel texture (i.e., uninformative regions). In this research study, a multi-stage method including Chan-Vese, color range ratio, adaptive gamma correction method (AGCM), canny color edge detection operator, and morphological processing is proposed to detect these uninformative regions. The results support the effectiveness of the proposed method. In conclusion, the proposed method is a simple method to implement and performed well in removing the uninformative regions of small bowel images.