Determination of subjective and objective similarity for pairs of masses on mammograms for selection of similar images

Presentation of images with known pathology similar to that of a new unknown lesion would be helpful for radiologists in their diagnosis of breast cancer. In order to find images that are really similar and useful to radiologists, we determined the radiologists' subjective similarity ratings for pairs of masses, and investigated objective similarity measures that would agree well with the subjective ratings. Fifty sets of images, each of which included one image in the center and six other images to be compared with the center image, were selected; thus, 300 pairs of images were prepared. Ten breast radiologists provided the subjective similarity ratings for each image pair in terms of the overall impression for diagnosis. The objective similarity measures based on cross-correlation of the images, differences in feature values, and psychophysical measures by use of an artificial neural network were determined. The objective measures based on the cross-correlation were found to be not correlated with the subjective similarity ratings (r 0.40). When several image features were used, the differences-based objective measure was moderately correlated (r = 0.59) with the subjective ratings. The relatively high correlation coefficient (r = 0.74) was obtained for the psychophysical similarity measure. The similar images selected by use of the psychophysical measure can be useful to radiologists in the diagnosis of breast cancer.