Fusion of white and gray matter geometry: a framework for investigating brain development.

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TitleFusion of white and gray matter geometry: a framework for investigating brain development.
Publication TypeJournal Article
Year of Publication2014
AuthorsSavadjiev, P, Rathi, Y, Bouix, S, Smith, AR, Schultz, RT, Verma, R, Westin, C-F
JournalMed Image Anal
Volume18
Issue8
Pagination1349-60
Date Published2014 Dec
ISSN1361-8423
KeywordsDiffusion Tensor Imaging, Gray Matter, Humans, Image Interpretation, Computer-Assisted, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, Subtraction Technique, White Matter
Abstract

Current neuroimaging investigation of the white matter typically focuses on measurements derived from diffusion tensor imaging, such as fractional anisotropy (FA). In contrast, imaging studies of the gray matter oftentimes focus on morphological features such as cortical thickness, folding and surface curvature. As a result, it is not clear how to combine findings from these two types of approaches in order to obtain a consistent picture of morphological changes in both gray and white matter. In this paper, we propose a joint investigation of gray and white matter morphology by combining geometrical information from white and the gray matter. To achieve this, we first introduce a novel method for computing multi-scale white matter tract geometry. Its formulation is based on the differential geometry of curve sets and is easily incorporated into a continuous scale-space framework. We then incorporate this method into a novel framework for "fusing" white and gray matter geometrical information. Given a set of fiber tracts originating in a particular cortical region, the key idea is to compute two scalar fields that represent geometrical characteristics of the white matter and of the surface of the cortical region. A quantitative marker is created by combining the distributions of these scalar values using Mutual Information. This marker can be then used in the study of normal and pathological brain structure and development. We apply this framework to a study on autism spectrum disorder in children. Our preliminary results support the view that autism may be characterized by early brain overgrowth, followed by reduced or arrested growth (Courchesne, 2004).

DOI10.1016/j.media.2014.06.013
Alternate JournalMed Image Anal
PubMed ID25066750
PubMed Central IDPMC4162846
Grant ListR01 MH092862 / MH / NIMH NIH HHS / United States
R01 MH097979 / MH / NIMH NIH HHS / United States
R01 MH082918 / MH / NIMH NIH HHS / United States
P41 RR013218 / RR / NCRR NIH HHS / United States
R01 MH074794 / MH / NIMH NIH HHS / United States
P41 EB015902 / EB / NIBIB NIH HHS / United States
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