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Proceedings Paper

Using principal component analysis to visualize the spatial distribution of functional areas of the brain as studied with MRI during motor and sensory activation
Author(s): Finn Pedersen; Ewert W. Bengtsson; Tomas Hindmarsh; Bo Nordell; Hans Forssberg
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Paper Abstract

Magnetic resonance imaging (MRI) can be used for functional brain studies. The identification of areas with changed blood oxygenation level dependent (BOLD) signal is usually done by visually inspecting maps of different kinds created through different post-processing procedures of the acquired images. It is desirable that the maps have as good an image quality as possible, and principal component analysis (PCA) can be used for this task. PCA is a data- driven method which does not use information about the timing of the experiment, instead the variance-covariance structure of the image data set is analyzed. PCA results in linear combinations of the analyzed MR images called score images, and the possibility to use score images as functional maps is investigated and compared to another commonly used method.

Paper Details

Date Published: 1 May 1994
PDF: 9 pages
Proc. SPIE 2168, Medical Imaging 1994: Physiology and Function from Multidimensional Images, (1 May 1994); doi: 10.1117/12.174399
Show Author Affiliations
Finn Pedersen, Uppsala Univ. (Sweden)
Ewert W. Bengtsson, Uppsala Univ. (Sweden)
Tomas Hindmarsh, Karolinska Hospital (Sweden)
Bo Nordell, Karolinska Hospital (Sweden)
Hans Forssberg, Karolinska Hospital (Sweden)

Published in SPIE Proceedings Vol. 2168:
Medical Imaging 1994: Physiology and Function from Multidimensional Images
Eric A. Hoffman; Raj S. Acharya, Editor(s)

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