Figure 4.
Segmentation of Angiodysplasia colonoscopy images on sampled test images from the GIANA challenge dataset, generated via the kernel SVM using the VGG filter bank with the kernel feature selection. The bandwidth of RBF kernel 1/2σ2 is selected via maximum mean discrepancy optimization. Top: the colonscopy images obtained using Wireless Capsule Endoscopy (WCE), Middle: the heat maps depicting the soft-max of SVM kernel classifier, Bottom: the heat map of the residual image computed as the absolute difference between the proposed segmentation and the ground truth. Despite training on a small data-set, the kernel SVM performs well on the test data set.