Perfusion-based segmentation of the human brain using similarity mapping

In this work, a method for segmenting human brain MR scans on the basis of perfusion is described. This technique uses a measure of similarity between the time-intensity curves obtained with dynamic susceptibility contrast-en hanced MRI and a modeled curve of reference to isolate a tissue of interest , such as white or gray matter. The aim of this study was to validate the m ethod by performing segmentation of white and gray matter in six controls. The relative regional blood volume gray-to-white matter ratio was used as a criterion to assess the quality of segmentation, On average, this ratio wa s 2.1 +/- 0.2, which is in good agreement with the literature, thus suggest ing reliable segmentation. In the case of abnormal perfusion, time-intensit y curves are different in shape than that of normal tissue. Therefore, this approach might allow the segmentation of pathological regions, and combine d with an indicator-dilution analysis might offer new possibilities for cha racterizing a brain pathology. Magn Reson Med 45:261-268, 2001, (C) 2001 Wi ley-Liss, Inc.