Quantification of image quality using information theory

Aims of present study were to examine usefulness of information theory in visual assessment of image quality. We applied first order approximation of the Shannon's information theory to compute information losses (IL). Images of a contrast-detail mammography (CDMAM) phantom were acquired with computed radiographies for various radiation doses. Information content was defined as the entropy Σp( i )log(1/p ( i )), in which detection probabilities p ( i ) were calculated from distribution of detection rate of the CDMAM. IL was defined as the difference between information content and information obtained. IL decreased with increases in the disk diameters (P < 0.0001, ANOVA) and in the radiation doses (P < 0.002, F-test). Sums of IL, which we call total information losses (TIL), were closely correlated with the image quality figures (r = 0.985). TIL was dependent on the distribution of image reading ability of each examinee, even when average reading ratio was the same in the group. TIL was shown to be sensitive to the observers' distribution of image readings and was expected to improve the evaluation of image quality.