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An Efficient Finite Element Solution of the Generalised Bloch-Torrey Equation for Arbitrary Domains Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Using Automatic HARDI Feature Selection, Registration, and Atlas Building to Characterize the Neuroanatomy of Aβ Pathology

Authors : Evan Schwab, Michael A. Yassa, Michael Weiner, René Vidal

Published in: Computational Diffusion MRI

Publisher: Springer International Publishing

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Abstract

The detection of white matter microstructural changes using diffusion magnetic resonance imaging (dMRI) often involves extracting a small set of scalar features, such as fractional anisotropy (FA) and mean diffusivity (MD) in diffusion tensor imaging (DTI). With the advent of more advanced dMRI techniques, such as high angular resolution diffusion imaging (HARDI), a number of mathematically inspired new scalar features have been proposed. However, it is unclear how to select the most biologically informative combinations of features for biomarker discovery. This paper proposes an automatic HARDI feature selection algorithm which is based on registering HARDI features to feature atlases for optimal clinical usability in population studies. We apply our framework to the characterization of beta-amyloid (Aβ) pathology for the early detection of Alzheimer’s disease (AD) to better understand the relationship between Aβ pathology and degenerative changes in neuroanatomy.

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previous chapter Registration Strategies for Whole-Body Diffusion-Weighted MRI Stitching
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Metadata
Title
Using Automatic HARDI Feature Selection, Registration, and Atlas Building to Characterize the Neuroanatomy of Aβ Pathology
Authors
Evan Schwab
Michael A. Yassa
Michael Weiner
René Vidal
Copyright Year
2016
Book
Computational Diffusion MRI

Print ISBN: 978-3-319-28586-3

Electronic ISBN: 978-3-319-28588-7

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-28588-7_18

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