Segmentation of Image Using Watershed and Fast Level Set Methods

Abstract

AbstractTechnology is proliferating. Many methods are used for medical imaging .The important methods used here are fast marching and fast level set in comparison with the watershed transform .Since watershed algorithm was applied to an image has over clusters in segmentation . Both methods are applied to segment the medical images. First, fast marching method is used to extract the rough contours. Then fast level set method is utilized to finely tune the initial boundary. Moreover, Traditional fast marching method was modified by the use of watershed transform.The method is feasible in medical imaging and deserves further research. In the future, we will integrate level set method with statistical shape analysis to make it applicable to more kinds of medical images and have better robustness to noise.Categories and Subject DescriptorsI.4 Image Processing and Computer VisionGeneral TermsDesignExperimentationKeywordsSegmentationWatershed transformfast marching method and fast level set method