Keywords: Microstructure, White Matter, Spherical Deconvolution, Spatial Regularization
Motivation: Constrained Spherical Deconvolution (CSD) is a state-of-the-art method for estimating the fiber orientation distribution function (fODF) in white matter from diffusion MRI data. However, CSD faces limitations in resolving fiber crossings with small inter-fiber angles when using low spherical harmonic order and produces noisy fODFs when using high order.
Goal(s): This study aims to improve the stability and angular resolution of fODFs from CSD.
Approach: We extend the CSD estimation framework by including a spatial regularization term that promotes fiber continuity, using a J-invariant auto-calibrated total variation denoiser.
Results: The proposed method enhances fiber crossing estimation and reduces spurious fibers.
Impact: The improved stability of the proposed method enables the utilization of higher spherical harmonic orders, with a superior ability to solve complex fiber crossings. This work has the potential to increase the accuracy of fiber-tracking algorithms and brain connectivity estimations.
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