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Activity Number: 26
Type: Topic Contributed
Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Imaging
Abstract #315110
Title: Improved Activation Detection in fMRI
Author(s): Ranjan Maitra* and Alejandro Murua
Companies: Iowa State University and University of Montreal
Keywords: Ising model ; EM algorithm ; signal-to-noise ratio ; false discovery rate ; threshold methods ; clustering
Abstract:

Functional Magnetic Resonance Imaging (fMRI) provides a popular approach to imaging cerebral activation in response to stimuli. Reliably detecting activation is, however, not an easy proposition because only a very small proportions of voxels show true activation. These truly activated voxels are known to be spatially localized, yet incorporating this information is challenging to implement practically. We provide a model-based approach that incorporates spatial context in a practical and methodologically sound manner while postulating our a priori expectation that a certain proportion of voxels is truly active. Results on simulation experiments for different noise levels are very promising. The methodology is also illustrated on three-dimensional real-life experiments, with improved reliability of activation.


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