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Proceedings Paper

MRI brain tumor segmentation based on improved fuzzy c-means method
Author(s): Wankai Deng; Wei Xiao; Chao Pan; Jianguo Liu
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Paper Abstract

This paper focuses on the image segmentation, which is one of the key problems in medical image processing. A new medical image segmentation method is proposed based on fuzzy c- means algorithm and spatial information. Firstly, we classify the image into the region of interest and background using fuzzy c means algorithm. Then we use the information of the tissues' gradient and the intensity inhomogeneities of regions to improve the quality of segmentation. The sum of the mean variance in the region and the reciprocal of the mean gradient along the edge of the region are chosen as an objective function. The minimum of the sum is optimum result. The result shows that the clustering segmentation algorithm is effective.

Paper Details

Date Published: 30 October 2009
PDF: 6 pages
Proc. SPIE 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 74972N (30 October 2009); doi: 10.1117/12.832577
Show Author Affiliations
Wankai Deng, Huazhong Univ. of Science and Technology (China)
Wei Xiao, Huazhong Univ. of Science and Technology (China)
Chao Pan, Huazhong Univ. of Science and Technology (China)
Jianguo Liu, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 7497:
MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques
Faxiong Zhang; Faxiong Zhang, Editor(s)

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