Statistical Characterization of Radiological Images: Basic Principles and Recent Progress.

This paper surveys our current understanding of the statistical properties of radiological images and their effect on image quality. Attention is given to statistical descriptions needed to compute the performance of ideal or ideal-linear observers on detection and estimation tasks. The effects of measurement noise, random objects and random imaging system are analyzed by nested conditional averaging, leading to a three-term expansion of the data covariance matrix. Characteristic functionals are introduced to account for the object statistics, and it is shown how they can be used to compute the image statistics.