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Voxel-Based Morphometry and Its Application to Alzheimer’s Disease Study

  • Xingfeng Li
Chapter

Abstract

Voxel-based morphometry (VBM) is a method for comparing different subject groups, which has many clinical applications. For example, VBM has been applied to study abnormal structures in Alzheimer’s disease (AD). This method is based on high-resolution structural MRI (sMRI) processing. To begin with, we introduce major sMRI preprocessing steps for cross-sectional VBM analysis. Then we provide the statistical method for comparing gray matter images from two different groups. After that, we present an enhanced VBM (eVBM) method for sMRI data analysis. We also compare eVBM with conventional VBM using a large cohort AD dataset.

Apart from introducing cross-sectional VBM, we provide longitudinal VBM method which is superior to cross-sectional VBM method in that it can be used to investigate cause–effect relationship and evaluate the cerebral cortex changes over time. We take AD study as an example to show how to apply this method for clinical study. In addition, we address the cause–effect relationship between different brain regions using causality analysis method. Furthermore, we present the results and discuss the advantages and disadvantages of the method for AD study. Finally, we introduce briefly the AD classification and structural image covariance analysis.

Keywords

Voxel-based morphometry (VBM) Alzheimer’s disease (AD) Longitudinal data analysis Histogram match Structural MRI (sMRI) 

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Xingfeng Li
    • 1
  1. 1.Intelligent Systems Research CentreUniversity of UlsterLondonderryUK

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