Diffusion imaging is a non-invasive imaging technique which provides fascinating and valuable insights into the anatomy of the human brain. It has established a broad spectrum of clinically useful research studies and applications that focus on initiating therapies to ensure the best possible development, on monitoring the progression of diseases, and on planning neurosurgical interventions. Diffusion imaging is a non-invasive imaging technique that provides fascinating and valuable insights into the anatomy of the human brain. It has empowered a broad spectrum of clinical research studies and applications that focus on the improvement of therapeutic or diagnostic decisions, the monitoring or understanding of disease progression, or on the planning of neurosurgical interventions. This half-day course will provide attendees an overview on diffusion imaging techniques and related post-processing algorithms. Basic concepts of the diffusion-weighted MRI acquisition are given, followed by a comparison of different spherical diffusion functions which are used to represent the fiber direction of the underlying tissue. Fiber tracking, one of the most popular applications of diffusion imaging, will be explained with a focus on its reliability to reconstruct crossing, kissing, merging and fanning axonal fibers. Further parts of this course will explain quantitative approaches and advanced visualization techniques like fiber clustering, glyph rendering and illustrative visualization. Throughout this course, we pay attention to the validation by hardware phantoms and software phantoms and thoroughly discuss related literature on the inherent uncertainty of diffusion imaging. Clinical impact and challenges are explained, and a review will be made of existing publicly-available packages, focusing on topics such as usability, speed and extensibility. <i>This course is intended as a companion to SC1065, Exploring Brain Connectivity in-vivo: from Theory to Practice. Attendees will benefit maximally by attending both courses.</i>