Keywords: Diffusion Analysis & Visualization, Diffusion Tensor Imaging, Diffusion Denoising
Motivation: DTI suffers from intrinsic low SNR compared to conventional MRI, making denoising crucial.
Goal(s): Our study aims to introduce a novel filtration method based on an estimated pattern of areas most directionally affected in the spatial frequency domain.
Approach: A pattern was suggested through DTI theory and observations of simulation data. This was then used to propose a filter for noise reduction. The application of this filter was quantitatively and qualitatively evaluated on simulated MR and DTI images, considering added noise.
Results: The results showed not only the method’s increased robustness to noise but also a clearer representation of white matter tracts.
Impact: By integrating the fundamental concepts of diffusion within the white matter into our filter design, we present a promising approach to denoising DTI data, potentially yielding more reliable and biologically meaningful results, and benefiting researchers investigating brain connectivity.
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