Over the last two decades interest in diffusion MRI has exploded. This noninvasive technique provides unique measurements sensitive to the microstructure of living tissue and enables connectivity mapping of the brain. As microscopic tissue alterations are often the earliest signs of disease or regeneration, the variety of clinical applications is expanding rapidly and includes detection of lesions and damaged tissue, grading of cancerous tumours, prognosis of functional impairment and neurosurgical planning. Moreover, fibre tractography gives fundamental new insights into connectional neuroanatomy.
Computational techniques are key to the continued success and development of diffusion MRI and to its widespread transfer into the clinic. New processing methods are essential for addressing challenges at each stage of the diffusion pipeline: data acquisition, image reconstruction, biophysical modelling and model fitting, tissue microstructure mapping, fibre tracking and connectivity mapping, machine learning and deep neural networks, visualisation, group studies and statistical inference.
This full-day MICCAI 2018 workshop, now in the eleventh edition, will give a snapshot of the current state of the art. Particular focus will be given to the opportunities that novel approaches such as machine learning techniques provide for computational diffusion MRI inside and outside the brain.