Abstract
Brain imaging research with MRI spans a wide area, covering both structure and function, and ranging from basic research through clinical research to drug design and clinical trials. In recent years there has been a trend towards the collection of very large MRI databases which can allow for the detection of very small group-dependent effects. However, the logistical challenges of analysing such large datasets presents new challenges. This paper describes the “pipeline” framework developed at the Montreal Neurological Institute for the fully automated morphometric analysis of large brain imaging databases. The potential use of these techniques is illustrated by examples of their applications in multiple sclerosis, Alzheimer’s disease, and pediatric development.