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Detectability in computed tomographic images
Author(s) -
Hanson Kenneth M.
Publication year - 1979
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 - 10.1118/1.594534
Subject(s) - scanner , noise (video) , projection (relational algebra) , weighting , noise power , tomographic reconstruction , spectral density , iterative reconstruction , computed radiography , signal to noise ratio (imaging) , image noise , granularity , measure (data warehouse) , optics , mathematics , physics , image quality , algorithm , computer science , power (physics) , artificial intelligence , image (mathematics) , acoustics , statistics , database , operating system , quantum mechanics
The detection limitations inherent in statistically limited computed tomographic (CT) images are described through the application of signal detection theory. The detectability of large‐area, low‐contrast objects is shown to be chiefly dependent upon the low‐frequency content of the noise power spectral density. For projection data containing uncorrelated noise, the resulting ramplike, low‐frequency behavior of the noise power spectrum of CT reconstructions may be conveniently characterized by the number of noise‐equivalent x‐ray quanta (NEQ) detected in the projection measurements. The NEQ for a given image may be determined either from a measurement of the noise power spectrum or from the noise granularity computed with an appropriate weighting function. A measure of the efficiency of scanner dose utilization is proposed which compares the average dose to that required by an ideal scanner to obtain the same NEQ.