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2004
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Morphological Classification of Medical Images using Nonlinear Support Vector Machines

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Morphological Classification of Medical Images using Nonlinear Support Vector Machines
The wavelet decomposition of a high-dimensional shape transformation posed in a mass-preserving framework is used as a morphological signature of a brain image. Population differences with complex spatial patterns are then determined by applying a nonlinear support vector machine pattern classification method to the morphological signatures. By considering measurements from the entire image, and not only from isolated anatomical structures, and by using a highly non-linear classifier, this method has achieved very high classification results in a variety of tests.
Christos Davatzikos, Dinggang Shen, Zhiqiang Lao,
Added 20 Nov 2009
Updated 20 Nov 2009
Type Conference
Year 2004
Where ISBI
Authors Christos Davatzikos, Dinggang Shen, Zhiqiang Lao, Zhong Xue, Bilge Karaçali
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