Incorporation of Active Contour Without Edges in the Fast Level Set Framework for Biomedical Image Segmentation

In this paper we focus on the level set method for extracting object of interests in medical images, in particular the confocal microscopic images and magnetic resonance images (MRI). In this context, we have incorporated the active contour without edges in the fast level set without solving partial differential equation (PDE) framework in order to reduce the computational burden in the traditional level set method and to detect objects that are very close to each other and to use the advantages of active contour without the edges to detect the objects that are not defined by gradients. The results provided highlight the usefulness of the incorporation.