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Special Section Technical Briefs

Unsupervised Versus Supervised Methods for Categorizing Mental States From fMRI Data1

[+] Author and Article Information
Nasim Alamdari

Department of Electrical Engineering,
University of North Dakota,
Grand Forks, ND 58202

Shirin Akbari

Department of Biomedical Engineering,
Faculty of Medicine,
Shahid Beheshti University,
Tehran, Iran

Emad Fatemizadeh

School of Electrical Engineering,
Sharif University of Technology,
Tehran, Iran

Accepted and presented at The Design of Medical Devices Conference (DMD2015), April 13-16, 2015, Minneapolis, MN, USA.

Manuscript received March 3, 2015; final manuscript received March 17, 2015; published online April 24, 2015. Editor: Arthur Erdman.

J. Med. Devices 9(2), 020949 (Jun 01, 2015) (2 pages) Paper No: MED-15-1055; doi: 10.1115/1.4030128 History: Received March 03, 2015; Revised March 17, 2015; Online April 24, 2015

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References

Figures

Grahic Jump Location
Fig. 2

Mean discrimination performance of methods in subset of fMRI data, which is prepared by maximum distance feature generation

Grahic Jump Location
Fig. 1

Block diagram for classification and clustering functional MRI data

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