Diffusion coefficient orientation distribution function for diffusion magnetic resonance imaging

General orientation transform for the estimation of fiber orientations in white matter tissues

“…Here $$$ {\mathbf{q}}_{\mathbf{0}} $$$ is a unit vector ($$$ {\mathbf{q}}_{\mathbf{0}}^{\mathrm{T}}\cdotp {\mathbf{q}}_{\mathbf{0}}=1 $$$) in q‐space, $$$ \rho $$$ is the length of $$$ \mathbf{q}\left(|\mathbf{q}|=\rho \right) $$$, and $$$ a\left({\mathbf{q}}_{\mathbf{0}}\right) $$$ is defined as: $$$$ a\left({\mathbf{q}}_{\mathbf{0}}\right)=-\log \left(E\left({\mathbf{q}}_{\mathbf{0}}\right)\right)=\log \left({S}_0/S\left({\mathbf{q}}_{\mathbf{0}}\right)\right), $$$$ where $$$ S\left({\mathbf{q}}_{\mathbf{0}}\right) $$$ is the signal value associated with the unit vector $$$ {\mathbf{q}}_{\mathbf{0}} $$$ in q‐space, and $$$ {S}_0 $$$ is the signal without diffusion weighting. Equations ()–() are reformulations of our previous results 26 …”

“…Equations ( 3)-( 6) are reformulations of our previous results. 26 Therefore, the integral in (4) can be expressed as:…”

Diffusion kurtosis imaging and diffusion tensor imaging parameters applied to white matter and gray matter of patients with anti-N-methyl-D-aspartate receptor encephalitis

“…Based on the assumption that the diffusion of water molecules obeys a Gaussian distribution, DTI is the most widely used technique to assess white matter changes. However, due to the presence of cell membranes, neurons, and other organelles in tissues, the diffusion of water molecules obeys a non-Gaussian distribution (Shi et al, 2021); hence, the parameters of DTI, including mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD) and fractional anisotropy (FA), cannot describe water diffusion accurately. Diffusion kurtosis imaging (DKI) is regarded as a complementary technique for DTI, which can not only probe white matter changes accurately but can also assess the microstructural alternations in the gray matter which by the aggregation of many neuron cells and dendrites (Jensen et al, 2005).Studies have shown that the parameters of DKI, including mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK) and kurtosis fractional anisotropy (KFA) is more suitable for assessing microstructural changes of white matter and gray matter regions with complex fiber arrangements (Qiao et al, 2020;Thaler et al, 2021).…”

Utilizing the TractSeg Tool for Automatic Corticospinal Tract Segmentation in Patients With Brain Pathology

“…10 In recent years, several methods have been proposed for automatic fibers segmentation. Poulin et al proposed the use of a Feed-Forward Neural Network, and a Recurrent Neural Network for fibers segmentation, demonstrating high performers on the ISMRM 2015 segmentation challenge, 11 enabling to recover of more than 50% of the spatial coverage. 12 Lam et al 13 proposed the TRAFIC tool, and trained the arcuate fasciculus frontotemporal bundle on the right and left, reaching ∼52% and 70% of accuracy, respectively.…”