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A new brain MRI image segmentation strategy based on K-means clustering and SVM

  • Northwestern Polytechnical University Xian

科研成果: 书/报告/会议事项章节会议稿件同行评审

26 引用 (Scopus)

摘要

For the problem of noise and no reference image during brain magnetic resonance imagery (MRI) image segmentation, this paper proposes a new strategy to segment brain MRI image based on K-means clustering algorithm and support vector machine (SVM). Firstly, the strategy segments brain MRI image using K-means clustering algorithm to obtain the initial classification result as the class label, secondly, the feature vectors of each pixel of brain tissue are selected as the training samples and test samples, finally, brain MRI image is segmented by SVM. Experimental results show that the proposed segmentation strategy obtains better segmentation effect, especially has a good noise suppression for brain images with low signal-noise-ratio (SNR).

源语言英语
主期刊名Proceedings - 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2015
出版商Institute of Electrical and Electronics Engineers Inc.
270-273
页数4
ISBN(电子版)9781479986460
DOI
出版状态已出版 - 20 11月 2015
活动7th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2015 - Hangzhou, Zhejiang, 中国
期限: 26 8月 201527 8月 2015

出版系列

姓名Proceedings - 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2015
2

会议

会议7th International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC 2015
国家/地区中国
Hangzhou, Zhejiang
时期26/08/1527/08/15

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