title: Toward an automated analysis system for nuclear magnetic resonance imaging. II. Initial segmentation algorithm.
abstract: Image segmentation algorithms based on hierarchical clustering have been developed for analysis of T1 and T2 nuclear magnetic resonance images. Application of these algorithms to simultaneous T1-T2 images of healthy volunteers extracted fundamental tissue types in the brain. These algorithms also were used both to identify the extent of the region of involvement of a subject with a history of a grade 3 astrocytoma of the right frontal lobe of the brain, and to characterize the tissue within the region of involvement. These results suggest that a simple segmentation algorithm can produce reasonable clustering of tissue types within the brain.
mesh_terms: D001699:Biometry; D001921:Brain / Q000033:anatomy & histology*; D001932:Brain Neoplasms / Q000175:diagnosis; D005909:Glioblastoma / Q000175:diagnosis; D006283:Health Physics; D006801:Humans; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*