Segmentation of pathological features in MRI brain datasets

One of the major clinical applications of magnetic resonance imaging (MRI) is to detect pathological features in human body parts. While results are available in a digital format, their evaluation is performed by a trained human observer, which is still considered as the "gold standard". However, providing additional quantitative figures (e.g., lesion size or count) is tedious for a human and may better be obtained from automatical image processing methods. Three example brain lesion types (as revealed by MRI) and methods for their detection are described. Special emphasis is led on the way prior knowledge about the specific lesion type is incorporated in the algorithm.