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