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Activity Number:
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201
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Type:
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Contributed
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Date/Time:
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Monday, July 30, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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ENAR
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| Abstract - #310053 |
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Title:
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Modeling Progression of Cerebrovascular Disease with Longitudinal MRI Data
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Author(s):
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Qian Weng*+
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Companies:
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University of California, Davis
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Address:
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1072 Tanland Drive Apt 208, Palo Alto, CA, 94303,
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Keywords:
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transition model ; neuroimaging ; spatial correlation
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Abstract:
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Cerebrovascular disease (CVD) is associated with increased risk of cognitive decline. Magnetic resonance imaging (MRI) enables researchers to visualize abnormalities of cerebral white matter (WMH), a marker for CVD. We focus on the development of models for the progression of CVD via WMH as seen on sequential MRI. Data from a single MRI consist of measurements for several hundred thousand spatially defined voxels, each corresponding to a small volume of the brain. We assume we know the WMH status for each voxel and that biologically this damage is not repaired, but that errors may occur in the observed WMH data. We will present a model for analyzing these data, theoretical properties of the estimates, the small sample properties of the estimates based on simulations, and an application to data from sequential MRI obtained in a large scale longitudinal imaging study.
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- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
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