Diffusion MRI with Machine Learning

Diffusion-weighted magnetic resonance imaging (dMRI) offers unique capabilities such as noninvasive assessment of brain's micro-structure and structural connectivity. However, analyzing the dMRI data to extract useful information for clinical and scientific purposes is challenging. The dMRI measurements often suffer from strong noise and artifacts, there is usually high inter-session and inter-scanner heterogeneity in the data and considerable inter-subject variability in brain structure, and the relationship between measurements and the phenomena of interest can be highly complex. Recent years have witnessed …

assessment brain capabilities clinical connectivity cs.cv cs.lg data diffusion eess.iv extract imaging information machine machine learning micro mri noise noninvasive session