A new 3-D technique for the segmentation and quantification of human spontaneous intra-cerebral brain hemorrhage (ICH) is presented in this paper. The algorithm for ICH primary region segmentation uses the spatially weighted K-means histogram-based clustering algorithm. The ICH edema region segmentation algorithm employs an iterative morphological processing of the ICH brain data. A volume rendering technique is used for the effective 3-D visualization of ICH segmented regions. A computer program is developed for use in the human spontaneous ICH study involving a large number of patients. Experimental measurements and visualization results are presented which were computed on real ICH patient brain data.