Estimation of multiple fiber orientations from diffusion tensor MRI using independent component analysis

Determination of fiber orientation from diffusion tensor is problematic when the tensor is not linear anisotropic. Particularly planar anisotropy is often an indicator of multiple fibers in a voxel. A novel method has been developed to identify the orientations of multiple fiber tracts in a voxel of diffusion tensor magnetic resonance imaging (MRI) using independent component analysis (ICA). A computationally efficient algorithm to estimate the independent sources has been derived by introducing a new adaptive nonlinear function to model the cumulative distribution of the sources. Monte Carlo simulation was used to evaluate the method. Simulations suggest that the orientations of two tensors in a voxel can be estimated with mean error of less than 10° for most interfiber angles when the signal-to-noise ratio is higher than 30. A processing and source selection strategy has been proposed and successfully tested with simulated tensor fields incorporating fiber crossing and with human data. Qualitative assessment of the result from human data analysis demonstrated that the ICA method reasonably estimated multiple fiber orientations corresponding to anatomically known white matter tracts.