Volume 22, Issue 7 p. 1057-1061

Toward consensus on quantitative assessment of medical imaging systems

Charles E. Metz

Charles E. Metz

Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, The University of Chicago, Chicago, Illinois 60637

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Robert F. Wagner

Robert F. Wagner

Office of Science and Technology, Center for Devices and Radiological Health, Food and Drug Administration, Rockville, Maryland 20857

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Kunio Doi

Kunio Doi

Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, The University of Chicago, Chicago, Illinois 60637

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David G. Brown

David G. Brown

Office of Science and Technology, Center for Devices and Radiological Health, Food and Drug Administration, Rockville, Maryland 20857

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Robert M. Nishikawa

Robert M. Nishikawa

Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, The University of Chicago, Chicago, Illinois 60637

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Kyle J. Myers

Kyle J. Myers

Office of Science and Technology, Center for Devices and Radiological Health, Food and Drug Administration, Rockville, Maryland 20857

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First published: July 1995
Citations: 85

Abstract

Consensus has been developing over the past few decades on a number of measurements required for the laboratory assessment of medical imaging modalities. Nevertheless, understanding of the connection between these measurements and human observer performance in a broad range of tasks remains far from complete. Focusing primarily on projection radiography to provide concrete examples, this overview indicates areas in which consensus on methodology for physical image-quality measurement has been established. Concepts such as “noise equivalent quanta” (NEQ) and “detective quantum efficiency” (DQE) have been found useful for normalizing physical measurements on an absolute scale and for relating those measurements to the decision performance of a hypothetical “ideal observer” that effectively performs decision tasks from the image data. The connection between ideal observer performance and human performance, as determined by receiver operating characteristic (ROC) analysis, remains to be understood for many clinically relevant tasks.