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.
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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.
|Title:||A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features|
|Location:||Imperial Coll, London, ENGLAND|
|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 > Computer Science|
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