✦ LIBER ✦

Unsupervised feature dimension reduction for classification of MR spectra

✍ Scribed by R. Baumgartner; R. Somorjai; C. Bowman; T.C. Sorrell; C.E. Mountford; U. Himmelreich

Book ID: 103840082
Publisher: Elsevier Science
Year: 2004
Tongue: English
Weight: 299 KB
Volume: 22
Category: Article
ISSN: 0730-725X
DOI: 10.1016/j.mri.2003.08.033

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✦ Synopsis

We present an unsupervised feature dimension reduction method for the classification of magnetic resonance spectra. The technique preserves spectral information, important for disease profiling. We propose to use this technique as a preprocessing step for computationally demanding wrapper-based feature subset selection. We show that the classification accuracy on an independent test set can be sustained while achieving considerable feature reduction. Our method is applicable to other classification techniques, such as neural networks, support vector machines, etc.

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