Medical Image Segmentation using Level Sets

Abstract

Computer-aided diagnosis for pre-operative planning and post-operative outcome evaluation is widely considered an important topic for next-generation surgery. 3D models of the patients' anatomical structures can be highly valuable in this context. The accuracy of these models is strongly dependent on the classification and segmentation algorithms acting at the very first stage of the modelling chain. A promising class of segmentation algorithms is related to level set methods. Here, we briefly review some applications of level sets to medical image segmentation.