International Journal of Innovative Research in Computer Science and Technology
Year: 2014, Volume: 2, Issue: 6
First page : ( 56) Last page : ( 61)
Online ISSN : 2350-0557.
Article Tools: Print the Abstract | Indexing metadata | How to cite item | Email this article | Post a Comment
Pritesh G. Shah , Bharti W. Gawali
Functional magnetic resonance imaging (fMRI) has the ability to not only get insight into how human brain functions but also to study the human brain of normal and diseased subjects. One of the methods to analyze the fMRI data is univariate approach, another approach is Multivariate discriminative approach. However for classification, there exists number of statistical techniques. In this paper, we perform classification of fMRI data using Fishers Linear Discriminative Analysis (LDA). The re-substitution error for the LDA calculated to be 0.1875. It is concluded that, the data are consistent with the multivariate normal distribution.
[1] H. Mao and G. S. Berns, “MRI in the study of brain functions: clinical perspectives”, MedicaMundi, April 2002.
[2] Russell A. Poldrack, Jeanette A. Mumford, Thomas E. Nichols, “Handbook of functional MRI Data Analysis”, Cambridge Press, ISBN: 978-0-521-51766-9, 2011.
[3] Functional Imaging Biomedical Informatics Research Network (FBIRN): http://fbirnbdr.nbirn.net:8080/BDR/
[4] MATLAB R2012a Help Manual.
[5] S. Strother et al, “The quantitative evaluation of functional neuroimaging experiments: The NPAIRS data analysis framework”, NeuroImage, 15(4):747-771, 2002.
Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India
No. of Downloads: 5 | No. of Views: 1385