Parallele Datenakquisition zur Beschleunigung Diffusionsgewichteter Kernspintomographie mit Stimulierten Echos
TL;DRAbstract
Magnetic resonance imaging (MRI) experiments can be sensitised to the erratic thermal displacement of (water) molecules by the application of magnetic field gradients. The associated signal decay allows for the quantification of the Brownian motion in terms of diffusion coefficients. In linearly structured biological tissues such as brain white matter where cell boundaries of bundled nerve fibres restrict and hinder free propagation, a marked dependence of the results on the direction of the gradients can be observed, the highest diffusivity being measured parallel to the fibre orientation. On the comparatively course scale of the MRI resolution contrasted with the cellular level, some aspects of the molecular dynamics in simple anisotropic geometries have been successfully characterised by an average diffusion tensor whose main eigenvector then coincides with the material's principal direction. For the reliable determination of the model parameters, a considerable number of data sets
Chat with Paper
AI Agents for this Paper
Magnetic resonance imaging (MRI) experiments can be sensitised to the erratic thermal displacement of (water) molecules by the application of magnetic field gradients. The associated signal decay allows for the quantification of the Brownian motion in terms of diffusion coefficients. In linearly structured biological tissues such as brain white matter where cell boundaries of bundled nerve fibres restrict and hinder free propagation, a marked dependence of the results on the direction of the gradients can be observed, the highest diffusivity being measured parallel to the fibre orientation. On the comparatively course scale of the MRI resolution contrasted with the cellular level, some aspects of the molecular dynamics in simple anisotropic geometries have been successfully characterised by an average diffusion tensor whose main eigenvector then coincides with the material's principal direction. For the reliable determination of the model parameters, a considerable number of data sets
Keywords
Chat
Click to start Chat