  Segmentation of medical images using seeded region growing technique is
increasingly becoming a popular method because of its ability to involve
high-level knowledge of anatomical structures in seed selection process. Region
based segmentation of medical images are widely used in varied clinical
applications like visualization, bone detection, tumor detection and
unsupervised image retrieval in clinical databases. As medical images are
mostly fuzzy in nature, segmenting regions based intensity is the most
challenging task. In this paper, we discuss about popular seeded region grow
methodology used for segmenting anatomical structures in CT Angiography images.
We have proposed a gradient based homogeneity criteria to control the region
grow process while segmenting CTA images.
