Estimation of the noisy component of anatomical backgrounds

The knowledge of the relationship that links radiation dose and image quali ty is a prerequisite to any optimization of medical diagnostic radiology. I mage quality depends, on the one hand, on the physical parameters such as c ontrast, resolution, and noise, and on the other hand, on characteristics o f the observer that assesses the image. While the role of contrast and reso lution is precisely defined and recognized, the influence of image noise is not yet fully understood. Its measurement is often based on imaging unifor m test objects, even though real images contain anatomical backgrounds whos e statistical nature is much different from test objects used to assess sys tem noise. The goal of this study was to demonstrate the importance of vari ations in background anatomy by quantifying its effect on a series of detec tion tasks. Several types of mammographic backgrounds and signals were exam ined by psychophysical experiments in a two-alternative forced-choice detec tion task. According to hypotheses concerning the strategy used by the huma n observers, their signal to noise ratio was determined. This variable was also computed for a mathematical model based on the statistical decision th eory. By comparing theoretical model and experimental results, the way that anatomical structure is perceived has been analyzed. Experiments showed th at the observer's behavior was highly dependent upon both system noise and the anatomical background. The anatomy partly acts as a signal recognizable as such and partly as a pure noise that disturbs the detection process. Th is dual nature of the anatomy is quantified. It is shown that its effect va ries according to its amplitude and the profile of the object being detecte d. The importance of the noisy part of the anatomy is, in some situations, much greater than the system noise. Hence, reducing the system noise by inc reasing the dose will not improve task performance. This observation indica tes that the tradeoff between dose and image quality might be optimized by accepting a higher system noise. This could lead to a better resolution, mo re contrast, or less dose. (C) 1999 American Association of Physicists in M edicine. [S0094-2405(99)01807-6].