Computer-assisted bleeding detection in wireless capsule endoscopy images

Wireless capsule endoscopy (WCE) has revolutionized the diagnosis and treatment of gastrointestinal tract, especially the small intestine where traditional endoscopies can not reach. However, this new technology leads to the inspection of a large number of images, which is a time consuming process and also too hard by naked eyes for doctors. In this article we propose a new computerized method for bleeding detection in WCE images. We employ the second component of CIE Lab color space together with appropriate segmentation and enhancement techniques, involving an adaptive anisotropic diffusion (alike Perona Malik diffusion). As a result of this procedure, it is possible to devise four functions to discriminate between bleeding and normal regions, in WCE images. Experimental results on several medical datasets show that the new algorithm achieves a very good rate of success and promising performance for bleeding detection.