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Segmentation of image using watershed and fast level set methods

Published: 25 February 2011 Publication History

Abstract

Technology 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.

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      ICWET '11: Proceedings of the International Conference & Workshop on Emerging Trends in Technology
      February 2011
      1385 pages
      ISBN:9781450304498
      DOI:10.1145/1980022
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 25 February 2011

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      1. fast marching method and fast level set method
      2. segmentation
      3. watershed transform

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