Medical imaging research at scale

Lecturer: Dave Cash (UCL DRC)

In the past few years, the amount of medical imaging data available across the whole spectrum of health and bioscience research has skyrocketed, enabled many new applications and discoveries. Larger sample sizes help characterize the clinical heterogeneity of the population and identify small but meaningful changes, particularly in individuals who are at-risk or showing the earliest signs of disease. In addition, they also are often needed to train and test machine learning and deep learning algorithms. However, the logistics of managing and analysing imaging data grow in complexity as the size of the data increases. Cloud-based and federated solutions can alleviate some of these issues but also bring new challenges