A tract-specific framework for white matter morphometry combining macroscopic and microscopic tract features |
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Authors: | Hui Zhang Suyash P Awate Sandhitsu R Das John H Woo Elias R Melhem James C Gee Paul A Yushkevich |
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Institution: | 1. National Engineering Laboratory for Video Technology, Peking University, Beijing, China;2. National Laboratory of Pattern Recognition, Chinese Academy of Sciences, Beijing, China;3. Department of Computer Science, University of Texas at San Antonio, San Antonio, USA;1. Department of Computer Science, University of Massachusetts Lowell, MA, USA;2. Department of Applied Mathematics, University of Colorado Boulder, CO, USA |
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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. |
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