Recently, we have shown that Independent Component Analysis (ICA) can be used to recover up to three distinct fiber directions per voxel by using diffusion MRI data with 25 gradient directions. One prerequisite of our ICA approach is that the number of fiber directions per voxel be known. In this paper, we present a method to extract voxels with zero to three fiber directions and classify them accordingly using diffusion MRI data. The approach relies on the SPM segmented white matter images as well as diffusion anisotropic values per voxel. K-means segmentation and constrained non-linear optimization techniques are used to classify voxels into one to three fiber directions. The diffusion model for optimization is based on the hierarchy of diffusion characteristics. The method is tested with a healthy human subject. It is observed that the fiber maps are consistent with the underlying brain anatomy.
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