NDLI: On clustering fMRI using potts and mixture regression models

Content Provider	IEEE Xplore Digital Library
Author	Jing Xia Feng Liang Wang, Y.M.
Copyright Year	2009
Description	Author affiliation: Departments of Statistics, Psychology and Bioengineering, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA (Wang, Y.M.) \|\| Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL 61820, USA (Jing Xia; Feng Liang)
Abstract	In this paper, we propose a model based clustering method for functional magnetic resonance imaging (fMRI) data to detect the functional connectivity network. The Potts model, which represents spatial interactions of neighboring voxels, is introduced to integrate the temporal mixture regression modeling into one single unified model. The estimation of the parameters is achieved through a restoration maximization (RM) algorithm for computation efficiency and accuracy. Additional features of our method include: the optimal number of clusters can be automatically determined; global trends and informative paradigms of the data are extracted by a dimension reduction algorithm based on principal component analysis (PCA) and a statistical significance test. Experimental results demonstrate that our approach can lead to robust and sensitive detection of functional networks.
Starting Page	4795
Ending Page	4798
File Size	628431
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5332641
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Principal component analysis Independent component analysis Parameter estimation Brain modeling Personal communication networks Clustering methods Magnetic resonance imaging Clustering algorithms USA Councils Data mining
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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