Clustering-Based Framework for Comparing fMRI Analysis Methods

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Clustering-Based Framework for Comparing fMRI Analysis Methods
In this paper, a cluster-based framework is introduced for comparing analysis methods of functional magnetic resonance images (fMRI). In the proposed framework, fMRI data is replaced with a feature space and each method considered as a clustering method in the new space. As a result, different methods can be compared by means of a cluster validity measure. The feature space is computed using a non-parametric method (principal component analysis-PCA). Four subjects have been analyzed with three methods and the proposed cluster-based framework has evaluated performance of the methods. The results are identical to those of the modified receiver operating characteristics (ROC). This validates the proposed approach.
Hamid Soltanian-Zadeh, Gholam-Ali Hossein-Zadeh, A
Added 20 Nov 2009
Updated 20 Nov 2009
Type Conference
Year 2004
Where ISBI
Authors Hamid Soltanian-Zadeh, Gholam-Ali Hossein-Zadeh, Ali-Mohammad Golestani
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