Computerized scheme for evaluating mammographic phantom images.
PURPOSE
The authors developed a computer algorithm to automatically evaluate images of the American College of Radiology (ACR) mammography accreditation phantom.


METHODS
The developed algorithm consist of the edge detection of wax insert, nonuniformity correction of background, and correction for magnification and also calculate the cross-correlation coefficient by image matching technique. The algorithm additionally evaluates target shape for fibers, target contrast for speck groups, and target circularity for masses. To obtain an ideal template image without noise and spatial resolution loss, the wax insert containing the embedded test pattern was extracted from the phantom and radiographed. Two template images and ten test phantom images were prepared for this study. The results of evaluation using the algorithm outputs were compared with the averaged results of observer studies by six skilled observers.


RESULTS
In comparing the results from the algorithm outputs with the results of observers, the authors found that the computer outputs were well correlated with the evaluations by observers, and they indicate the quality of the phantom image. The correlation coefficients between results of observer studies and two outputs of computer algorithm, i.e., the cross-correlation coefficient by template matching and indices of target shape for fibers, were 0.89 (95% confidence interval, 0.82-0.93; hereinafter the same) and 0.85 (0.76-0.91). The correlation coefficients between observer's results and two outputs: the cross-correlation coefficient and indices of target contrast for speck groups, were 0.83 (0.79-0.86) and 0.85 (0.81-0.88) and between observer's results and two outputs: the cross-correlation coefficient and indices of target circularity for masses, were 0.90 (0.84-0.94) and 0.87 (0.77-0.92).


CONCLUSIONS
Image evaluation using the ACR phantom is indispensable in quality control of a mammography system. The proposed algorithm is useful for quality control and image evaluation of mammography units.