Psych~utry Research: ~eurai~agi~g, 4533-51 Elsevier 33 Segmentation Techniques for the Classification of Brain Tissue Using Magnetic Resonance Imaging Gregg Cohen, Nancy C. Andreasen, Randall Alliger, Stephan Arndt, James Kuan, William T.C. Yuh, and James Ehrhardt Received November 14, 1991; revised version received February 26, 1992: accepted March 1. 1992. zyxwvutsrqponmlkjihgfedcbaZYXWVUTSRQPONMLKJIHGFEDCBA Abstract. A technique is described for classifying brain tissue into three components: gray matter, white matter, and cerebrospinal fluid. This technique uses simultaneously registered proton density and T,-weighted images. Samples of each of the three types of tissue are identified on both image sets and used as “training classes”; these tissue samples are then used to generate a linear discriminant function, which is used to classify the remaining pixels in the image data set. Effects of varying the location and number of training classes have been explored; six pairs of training classes have been found to yield a suitable classification. Interrater and test-retest reliability have been examined and found to be good. Intrascanner and interscanner reproducibility has also been evalu- ated; classification rates are reproducible within the same individual when the same scanner is used, but in this study poor reproducibility occurs when the same individual is scanned on two different scanners. The vaiidity of the technique has been tested by examining CorreIations between traced and segmented regions of interest, evaluating ~o~elations with age, and conducting phantom studies, in addition to using visual inspection of the classified images as an indication of face validity. From all four perspectives, the method has been found to have good validity. Additional applications, strengths, and limitations are discussed. Key Words. Gray matter, white matter, cerebrospinal fluid, image processing. Before the advent of modern neuroimaging methods such as magnetic resonance (MR), post-mortem techniques were the only ones available to evaluate the integrity of brain structure and to attempt to make pathophysiological correlates with disease states. The disadvantages of post-mortem study are multiple and obvious. Because of its superb anatomic resolution, its capacity to image in multiple planes, and its potential for making repeated evaluations over time, MR provides an unparalleIed opportunity to study diseases of the central nervous system and to observe their neuropathological evolution. Gregg Cohen, MS., is Research Scientist, Department of Psychiatry; Nancy C. Andreasen, M.D., Ph.D., is Professor of Psychiatry and Director, Mental Health Clinical Research Center; Randall Alliger, Ph.D., is Research Scientist, Department of Psychiatry; Stephan Arndt, Ph.D., is Research Scientist, Department of Psychiatry; and James Kuan, M.D., is Postdoctoral Fellow, Mental Health Clinical Research Center, Department of Psychiatry, The University of Iowa Hospitals and Clinics, Iowa City, IA. William T.C. Yuh, M.D., E.E., and James Ehrhardt, Ph.D., are Professors of Radiology, Department of Radiology, The University of Iowa Hospitals and Clinics, Iowa City, IA. (Reprint requests to Dr. N.C. Andreasen, University of Iowa Hospitals and Clinics, MHCRC, 2711 JPP, 200 Hawkins Dr., Iowa City, IA 52242, USA.) 0161781/92/$05.~ @ I992 Elsevier Scientific Publishers Ireland Ltd.