Segmentation and Tissue Characterization in MR Imaging

Diffusion-weighted imaging enables the diagnosis of cerebral ischemias very early, thus supporting therapies such as thrombolysis. However, morphology and tissue-characterizing parameters (e.g. relaxation times or water diffusion) may vary strongly in ischemic regions, indicating different underlying pathologic processes. As the determination of the parameters by a supervised segmentation is very time consuming, we evaluated how different infarct patterns may be segmented interactively by snakes or automatically by a multidimensional feature-based method.

To ensure a routinely use of the methods, the analyses of their performance using input data aquired in the clinical settings is a main focus of the work. Therefore a standardized data set was composed for statistic analyses and quantitative evaluation. It consists of synthetic images and results of  supervised segmentations for data sets of 64 patients.