Ghosh T, Fattah S A, Shahnaz C, Wahid K A
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:4683-6. doi: 10.1109/EMBC.2014.6944669.
Wireless capsule endoscopy (WCE) is one of the most effective technologies to diagnose gastrointestinal (GI) diseases, such as bleeding in GI tract. Because of long duration of WCE video containing large number images, it is a burden for clinician to detect diseases in real time. In this paper, an automatic bleeding image detection method is proposed utilizing construction of an index image incorporating certain level of information from each plane of RGB color space. Distinguishable color texture feature is developed from index image by histogram. Support vector machine (SVM) classifier is employed to detect bleeding and non-bleeding images from WCE videos. From extensive experimentation on real time WCE video recordings, it is found that the proposed method can accurately detect bleeding images with high sensitivity and specificity.
无线胶囊内镜(WCE)是诊断胃肠道(GI)疾病(如胃肠道出血)最有效的技术之一。由于WCE视频持续时间长且包含大量图像,临床医生实时检测疾病负担较重。本文提出了一种自动出血图像检测方法,该方法利用从RGB颜色空间的每个平面合并一定水平信息来构建索引图像。通过直方图从索引图像中提取可区分的颜色纹理特征。采用支持向量机(SVM)分类器从WCE视频中检测出血和非出血图像。通过对实时WCE视频记录进行大量实验发现,该方法能够以高灵敏度和特异性准确检测出血图像。