Fuzzy Cluster Method based on RV measure for functional MRI data analysis

DOI

10.2991/iccsee.2013.101How to use a DOI?

Keywords

fMRI, FCA, Pearson coefficient, RV coefficient

Abstract

Functional magnetic resonance imaging (fMRI) has become one of the important tools of functional connectivity studies of the human brain. Fuzzy clustering method (FCM) is a common method for analysis of fMRI data. Traditional FCA methods measure the similarity between the BOLD time course of a centroid and the ones of all other voxels in the brain on the basis of Pearson correlation coefficient. This article puts forward a multi-voxel-based RV coefficient similarity measure to overcome the defects of traditional similarity distance measure in FCM. The experimental results show that the RV-based FCA method has not only improved the speed of FCA, but has comparatively raised the accuracy of the method.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Han Wang
AU  - Weiming Zeng
PY  - 2013/03
DA  - 2013/03
TI  - Fuzzy Cluster Method based on RV measure for functional MRI data analysis
BT  - Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)
PB  - Atlantis Press
SP  - 394
EP  - 397
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccsee.2013.101
DO  - 10.2991/iccsee.2013.101
ID  - Wang2013/03
ER  -