Bleeding detection in wireless capsule endoscopy videos - Color versus texture features.
Wireless capsule endoscopy (WCE) is an effective technology that can be used to make a gastrointestinal (GI) tract diagnosis of various lesions and abnormalities. Due to a long time required to pass through the GI tract, the resulting WCE data stream contains a large number of frames which leads to a tedious job for clinical experts to perform a visual check of each and every frame of a complete patient's video footage. In this paper, an automated technique for bleeding detection based on color and texture features is proposed. The approach combines the color information which is an essential feature for initial detection of frame with bleeding. Additionally, it uses the texture which plays an important role to extract more information from the lesion captured in the frames and allows the system to distinguish finely between borderline cases. The detection algorithm utilizes machine-learning-based classification methods, and it can efficiently distinguish between bleeding and nonbleeding frames and perform pixel-level segmentation of bleeding areas in WCE frames. The performed experimental studies demonstrate the performance of the proposed bleeding detection method in terms of detection accuracy, where we are at least as good as the state-of-the-art approaches. In this research, we have conducted a broad comparison of a number of different state-of-the-art features and classification methods that allows building an efficient and flexible WCE video processing system.
['Pogorelov|Konstantin|K|', 'Suman|Shipra|S|', 'Azmadi Hussin|Fawnizu|F|', 'Saeed Malik|Aamir|A|', 'Ostroukhova|Olga|O|', 'Riegler|Michael|M|', 'Halvorsen|Pål|P|', 'Hooi Ho|Shiaw|S|', 'Goh|Khean-Lee|KL|']
D000465:Algorithms D053704:Capsule Endoscopy D003116:Color D006471:Gastrointestinal Hemorrhage D041981:Gastrointestinal Tract D006801:Humans D000069550:Machine Learning D010363:Pattern Recognition, Automated D014741:Video Recording D059015:Wireless Technology
bleeding detection wireless capsule endoscopy texture feature color feature machine learning