FCM Segmentation Algorithm Research for CT Cerebrovascular Medical Image Based on Sober Extraction Algorithm

Abstract:

In this paper, linking with the basic principle of FCM (Fuzzy c-means clustering) algorithm, on the basis of theory research, a method of the cluster analysis of FCM based on sober extraction algorithm is proposed. To insure the quality of image reconstruction and the edge information extraction, the characters of sober operator is analyzed. Firstly, the approximate optimal solution obtained by the improved FCM algorithm is taken as the original value, then combined with intensity-texture-position feature space in order to produce connected regions shown in the image. The final segmentation result is achieved at last. The experiment results prove that in the view of the image segmentation, this segmentation algorithm based on sober extraction algorithm provides fast segmentation with high perceptual segmentation quality.

• Periodical: Applied Mechanics and Materials (Volumes 263-266)
• Pages: 2203-2206
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.263-266.2203
• Online since: December 2012
• Authors: Bin Liu*, Long Wang, Hai Yan Liu
• Keywords: Cerebrovascular Medical Image, FCM, Image Segmentation, Sober Extraction Algorithm

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