Magnetic Resonance Brain Imaging
Modeling and Data Analysis Using R
Chapter: Diffusion-Weighted Imaging
Diffusion weighted Magnetic Resonance Imaging (dMRI) has long proven to be a versatile tool for the in-vivo micro structural investigation of the human brain, the spinal cord, or even muscle tissue. In contrast to conventional weighted MRI or functional MRI discussed in the preceding Chapter it is quantitative in the sense, that it directly infers on physical quantities with physical units, specifically the diffusion constant. In this chapter, we will first elaborate on the physical background before presenting experimental dMRI data and describe its processing. This includes pre-processing steps, i.e. the removal of artifacts, and the actual modeling of the data to infer on interesting and relevant quantities. We also discuss a structural adaptive smoothing method for dMRI data before concluding the chapter with fiber tracking within the brain white matter and the construction of structural connectivity networks.