A Method for Shape Analysis and Segmentation in MRI

Morphometry of human magnetic resonance images (MRI) is the process of measuring structural variations that occur in the brain. Morphometrics provide a mechanism to monitor and relate structural changes of anatomy to the onset or progression of a disease. It is therefor a very important area of research, specifically since MRI sequences are non-invasive and can be acquired in-vivo. This paper addresses two sub-problems in the area of MRI morphometry: 1) shape analysis and 2) semi-automated segmentation. Firstly the paper presents a method of analysing for group differences between 2D contours. The theoretical underpinning is derived from the field of content-based image retrieval, specifically to solve contour correspondences. Secondly the paper uses these correspondences to train a deformable model to automatically segment structures. This is achieved using a modified active appearance model fitting algorithm.