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Activity Number:
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144
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2007 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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| Abstract - #310357 |
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Title:
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Correlation Analysis Between Two Sets of Brain Images
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Author(s):
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Yeming Ma*+
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Companies:
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State University of New York at Stony Brook
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Address:
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19 Quaker Hill Road, Stony Brook, NY, 11790,
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Keywords:
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Correlation ; 3D brain image ; normalization ; PET-FDG ; statistical parametric mapping (SPM) ; voxel
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Abstract:
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We propose a method in search for brain regions that have significant correlation between two sets of 3D brain images. It extended the capability of the existing SPM software and is generally applicable to any images. Two preprocessing steps were exacerbated from SPM, spatial normalization to a standard brain template and spatial smoothing for multiple comparison correction. We compute the correlation coefficient from the preprocessed images using a "same location strategy" at each voxel to obtain a correlation r-map. Similar to SPM activation concept, activated regions were defined above a threshold calculated from a p-value selected by users. As an example we analyzed brain glucose metabolic images (PET-FDG) taken on treatment and placebo conditions. Correlation maps were computed for 21 cocaine-addictive and 16 healthy control subjects.
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