Paper Title:
Novel Method of MRI Medical Image Segmentation Combining Watershed Algorithm and WKFCM Algorithm
  Abstract

Aimed at the disadvantage of over-segmentation that traditional watershed algorithm segmented MRI images, a new method of MRI image segmentation was presented. First, through traditional watershed segmentation algorithm, the image was segmented into different areas, and then based on the improved kernel-clustering algorithm, we used Mercer-kernel to map average gray value of each area to high-dimensional feature space, making originally not displayed features manifested. In this way, we can achieve a more accurate clustering, and solve over-segmentation problem of watershed algorithm segmenting MRI images efficiently, thereby get better segmentation result. Experimental results show that the method of this paper can segment brain MRI images satisfactorily, and obtain clearer segmentation images.

  Info
Periodical
Chapter
Chapter 8: System Modeling and Simulation
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
4518-4522
DOI
10.4028/www.scientific.net/AMM.121-126.4518
Citation
J. Q. Liu, K. Chen, "Novel Method of MRI Medical Image Segmentation Combining Watershed Algorithm and WKFCM Algorithm", Applied Mechanics and Materials, Vols. 121-126, pp. 4518-4522, 2012
Online since
October 2011
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Price
$32.00
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