Zhang, H;
Awate, SP;
Das, SR;
Woo, JH;
Melhem, ER;
Gee, JC;
Yushkevich, PA;
(2010)
A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features.
MEDICAL IMAGE ANALYSIS
, 14
(5)
666 - 673.
10.1016/j.media.2010.05.002.
Abstract
Diffusion tensor imaging plays a key role in our understanding of white matter both in normal populations and in populations with brain disorders. Existing techniques focus primarily on using diffusivity-based quantities derived from diffusion tensor as surrogate measures of microstructural tissue properties of white matter. In this paper, we describe a novel tract-specific framework that enables the examination of white matter morphometry at both the macroscopic and microscopic scales. The framework leverages the skeleton-based modeling of sheet-like white matter fasciculi using the continuous medial representation, which gives a natural definition of thickness and supports its comparison across subjects. The thickness measure provides a macroscopic characterization of white matter fasciculi that complements existing analysis of microstructural features. The utility of the framework is demonstrated in quantifying white matter atrophy in Amyotrophic Lateral Sclerosis, a severe neurodegenerative disease of motor neurons. We show that, compared to using microscopic features alone, combining the macroscopic and microscopic features gives a more complete characterization of the disease. (C) 2010 Elsevier B.V. All rights reserved.
| Type: | Article |
|---|---|
| Title: | A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features |
| Location: | Imperial Coll, London, ENGLAND |
| DOI: | 10.1016/j.media.2010.05.002 |
| Keywords: | White matter, Tract-specific morphometry, Shape analysis, Diffusion tensor MRI, Amyotrophic lateral sclerosis, CONTINUOUS MEDIAL REPRESENTATION, AMYOTROPHIC-LATERAL-SCLEROSIS, DIFFUSION-TENSOR MRI, HUMAN BRAIN, SPATIAL STATISTICS, TRACKING, IMAGES, MICROSTRUCTURE, ORIENTATION, BOUNDARIES |
| UCL classification: | UCL > School of BEAMS > Faculty of Engineering Science UCL > School of BEAMS > Faculty of Engineering Science > Computer Science |
| URI: | http://discovery.ucl.ac.uk/id/eprint/192085 |
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