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Morphology and Morphometry of Human Chronic Spinal Cord Injury Using Diffusion Tensor Imaging and Fuzzy Logic
Authors:Benjamin M. Ellingson  John L. Ulmer  Brian D. Schmit
Affiliation:(1) Department of Biomedical Engineering, Marquette University, P.O. Box 1881, Milwaukee, WI 53201-1881, USA;(2) Department of Radiology, Medical College of Wisconsin, Milwaukee, USA
Abstract:Diffusion tensor imaging (DTI) was performed on regions rostral to the injury site in four human subjects with chronic spinal cord injury (SCI) and equivalent regions in four neurologically intact subjects. Apparent diffusion coefficients were measured and compared between subjects. A fuzzy logic tissue classification algorithm was used to segment gray and white matter regions for morphometric analysis, including comparisons of cross-sectional areas of gray and white matter along with frontal and sagittal diameters. Results indicated a general decrease in both longitudinal and transverse diffusivity in the upper cervical segments of subjects with chronic SCI. Further, a decrease in the cross-sectional area of the entire spinal cord was observed in subjects with SCI, consistent with severe atrophy of the spinal cord. These observations have implications in tracking the progression of SCI from the acute to the chronic stages. We conclude that DTI with fuzzy logic tissue classification has potential for monitoring morphological changes in the spinal cord in people with SCI.
Keywords:Diffusion tensor imaging  Spinal cord injury  Fuzzy logic
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