title: Bleeding detection in wireless capsule endoscopy images based on color invariants and spatial pyramids using support vector machines.
abstract: Wireless capsule endoscopy (WCE) is a revolutionary imaging technique that enables detailed inspection of the interior of the whole gastrointestinal tract in a non-invasive way. However, viewing WCE videos is a very time-consuming, and labor intensive task for physicians. In this paper, we propose an automatic method for bleeding detection in WCE images. A novel series of descriptors which combine color and spatial information is designed in a way that local and global features are also incorporated together. And a kernel based classification method using histogram intersection or chi-square is deployed to verify the performance of the proposed descriptors. Experiments demonstrate that the proposed kernel based scheme is very effective in detecting bleeding patterns of WCE images.
authors.affiliation: School of Electronics, Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China. 1090359015@sjtu.edu.cn
authors.forename: Guolan
authors.initials: G
authors.lastname: Lv
authors.forename: Guozheng
authors.initials: G
authors.lastname: Yan
authors.forename: Zhiwu
authors.initials: Z
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D053704:Capsule Endoscopy / Q000379:methods*; D003116:Color; D001330:Electronic Data Processing; D041981:Gastrointestinal Tract / Q000473:pathology; D006470:Hemorrhage / Q000175:diagnosis*; D006801:Humans; D015233:Models, Statistical; D012815:Signal Processing, Computer-Assisted; D060388:Support Vector Machine; D014456:Ulcer / Q000473:pathology; D014741:Video Recording; D059015:Wireless Technology