FCM based automatic thresholding algorithm to segment the brain MR image

被引:0
|
作者
Cheng, Cfiing-Hsue [1 ]
Chen, You-Shyang [1 ]
Lin, Tzu-Cheng [1 ]
机构
[1] Natl Yunlin Univ Sci & Technol, Dept Informat Management, Touliu 640, Yunlin, Taiwan
来源
PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2007年
关键词
fuzzy c-means; Magnetic Resonance Image; segmentation;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Segmenting the various brain tissues is very valuable in the analysis of brain MR image data, and has a wide range or applications involving clinical analysis, visual inspection etc., it is a challenging due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. A simple automatic thresholding algorithm based on FCM for segmentation of brain MR image is developed. The thresholds, determined by the information of the result or FCM and Otsu' s thresholding method, is used to extract cerebrum region (interesting region), and segment it by FCM. This paper performs the uniformity measure to the segmented image. The results show that the quality of interesting region of segmented images is satisfied. The proposed segmentation algorithm can not only overcome the noise or image, but also can extract the cerebrum region and segment.
引用
收藏
页码:1371 / 1376
页数:6
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