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Toward an automated analysis system for nuclear magnetic resonance imaging. II. Initial segmentation algorithm
Author(s) -
O'Donnell M.,
Gore J. C.,
Adams W. J.
Publication year - 1986
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.595916
Subject(s) - magnetic resonance imaging , medical imaging , segmentation , nuclear magnetic resonance , algorithm , image segmentation , physics , computer science , nuclear medicine , artificial intelligence , medicine , radiology
Image segmentation algorithms based on hierarchical clustering have been developed for analysis of T 1 and T 2 nuclear magnetic resonance images. Application of these algorithms to simultaneous T 1 – T 2 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.