Abstract
A reoccurring theme in the diffusion tensor imaging literature is the per-voxel estimation of a symmetric 3 x 3 tensor describing the measured diffusion. In this work we attempt to generalize this approach by calculating 2 or 3 or up to k diffusion tensors for each voxel. We show that our procedure can more accurately describe the diffusion particularly when crossing fibers or fiber-bundles are present in the datasets.
Publication types
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Evaluation Study
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Research Support, N.I.H., Extramural
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Research Support, Non-U.S. Gov't
MeSH terms
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Algorithms*
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Artificial Intelligence*
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Brain / anatomy & histology*
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Diffusion Magnetic Resonance Imaging / methods*
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Humans
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Image Enhancement / methods
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Image Interpretation, Computer-Assisted / methods*
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Nerve Fibers, Myelinated / ultrastructure*
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Neural Pathways / anatomy & histology*
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Pattern Recognition, Automated / methods*
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Reproducibility of Results
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Sensitivity and Specificity
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Signal Processing, Computer-Assisted