Segmentation of Mr Brain Images through Discriminant Analysis
نویسندگان
چکیده
Nonparametric discriminant analysis methods are considered to segment brain multispectral MR images. Methods are based on i) a nonparametric estimate of voxel density functions by Kernel regression; ii) possibly a transform of the multispectral voxels into principal or independent components; iii) a classic Bayes 0-1 classification rule. Experiments are shown based on synthetic (brainweb) and real patient data. Comparison with parametric discriminant analysis is also shown.
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