In this study, we test a new method to automatically search for matched regions in bilateral digitized mammograms and to compute differences in region conspicuities in pairs of matched regions. One hundred pairs of bilateral images of the same view were selected for the experiment. Each pair of images depicted one verified mass. These 100 mass regions, along with 356 suspicious but actually negative mass regions, were first detected by a single-image-based CAD scheme. To find the matched regions in the corresponding bilateral images, a Procrustean-type technique was used to register the two images, which corrects the deformation of tissue structure between images by guaranteeing the registration of nipples, skin lines, and chest walls. Then, a region growth algorithm was applied to generate a growth region in the matched area, which has the same effective size as the suspicious region in the abnormal image. The conspicuities in the two matched regions, as well as their differences, were computed. Using the conspicuity in the original mass regions and the difference of conspicuities in the two matched regions as two identification indices to classify this set of 456 suspicious regions, the computed areas under the ROC curves (Az) were 0.77 and 0.75, respectively. This preliminary study indicates that by comparing the difference of conspicuities in two matched regions that a very useful feature for the CAD schemes can be extracted.