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This work presents an automated method for partitioning neuronal white matter (WM) into regions of interest with uniform WM architecture. These regions can then be used to replace atlas-derived regions for any subsequent statistical analysis. The fiber orientation distribution function is used as a model of WM architecture resulting in a voxel similarity function sensitive to both fiber orientations...
The growing clinical importance of diffusion tensor imaging (DTI) in disease investigation has prompted large population studies that require computational neuroanatomic techniques for tensor processing, as conventional analysis of scalar maps of DTI does not identify the full impact of pathology. In this paper we propose a comprehensive framework called manifold based morphometry (MBM) for the computational...
This paper addresses the problem of statistical analysis of diffusion tensor magnetic resonance images (DT-MRI). DT-MRI cannot be analyzed by commonly used linear methods, due to the inherent nonlinearity of tensors, which are restricted to lie on a nonlinear submanifold of the space in which they are defined, namely R6. We estimate this submanifold using the isomap manifold learning technique and...
This paper addresses the problem of statistical analysis of diffusion tensor magnetic resonance images (DT-MRI). DT-MRI cannot be analyzed by commonly used linear methods, due to the inherent non-linearity of tensors, which are restricted to lie on a non-linear sub-manifold of the space in which they are defined, namely IR . We perform statistical analysis on tensors by identifying the underlying...
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