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In this paper, we propose a new brain segmentation method for 3D magnetic resonance (MR) brain images. The proposed method consists of four steps: background rejection, image normalization, initial slice segmentation, and brain segmentation. In the image normalization step, intensity non-uniformity is removed. In the brain segmentation step, we use(More)
In a typical classification procedure of high dimensional data, feature extraction is first applied to reduce the dimensionality and a classifier is employed. However, in most feature extraction methods, covariance matrices must be estimated. When training samples are limited, this estimation is inherently biased, thereby generating ineffective features. In(More)
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