Regularized fuzzy c-means method for brain tissue clustering

Z. Hou; W. Qian; S. Huang; Q. Hu; W.L. Nowinski

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Regularized fuzzy c-means method for brain tissue clustering

机译：脑组织聚类的正则模糊c均值方法

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摘要

This paper presents a regularized fuzzy c-means clustering method for brain tissue segmentation from magnetic resonance images. A regularizer of the total variation type is explored and a method to estimate the regularization parameter is proposed.

机译：本文提出了一种从磁共振图像中进行脑组织分割的正则化模糊c均值聚类方法。探索了总变化类型的正则化器，并提出了估计正则化参数的方法。

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来源
《Pattern recognition letters》 |2007年第13期|1788-1794|共7页
作者
Z. Hou; W. Qian; S. Huang; Q. Hu; W.L. Nowinski;
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作者单位

Biomedical Imaging Lab, Singapore Bioimaging Consortium, 30 Biopolis Street, #07-01, Matrix, Singapore 138671, Singapore;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类自动化技术及设备;
关键词
fuzzy c-means; clustering; regularization; image segmentation; spatial modeling; noise level estimate;

机译：模糊c均值集群正规化;图像分割空间建模;噪声水平估计;

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6. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C-Means Clustering [O] . Ahmed Elazab, Changmiao Wang, Fucang Jia, 2015

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Regularized fuzzy c-means method for brain tissue clustering

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