Segmentation of medical images using geo-theoretic distance matrix in fuzzy clustering

Investigation on novel methods for extracting objects of interest in medical images has been an important and challenging area of research in image analysis. In particular, medical images are highly spatially correlated and subject to fuzzy distribution of pixels, we present in this paper a new algorithm for medical image segmentation with special reference to abdominal aortic aneurysm and degraded human brain imaging. Development of the new algorithm is based on the implementation of the theoretic distance matrix with spatial semi-variances.