A Statistical Dominance Algorithm for Edge Detection and Segmentation of Medical Images

This article proposes an algorithm which performs the initial stage of edge detection or segmentation. The algorithm counts the number of pixels with a given relation to the central point of the neighborhood. The output image is a statistical result of the dominance of points over their neighborhoods and allows the classification of these points to be determined (peak, valley, and slope). Therefore, this solution allows the impact of noise or uneven illumination in image results to be reduced. The basic features of the proposed algorithm are considered in this paper. Application of the algorithm is illustrated in the context of image segmentation of a corneal endothelium with a specular microscope, images of specimens of the brain tissue, and hand radiographs.