We are developing a bilateral pairing technique to help reduce false-positives identified by a single-view computer-aided detection (CAD) system for breast masses. In this study, we compare the performance of the proposed bilateral CAD to a single-view CAD. A database of 172 right/left breast pairs containing 205 biopsy-proven masses was used. Single-view CAD was run on each image using a lax selection threshold so that 5 objects per image were retained. The automated bilateral pairing algorithm identified all objects in a left breast mammogram "matching" a CAD detected object in the corresponding right breast image and visa-versa. Bilateral pairing was based on geometrical correspondence between objects with a matching score derived from a paired right/left object feature set and a linear discriminant analysis classifier. Leave-one out resampling was used to train/test the technique. We compared the FROC performances of the single-view CAD, the proposed bilateral technique and a modified CAD using manual pairing of bilateral structures. At a per-lesion detection sensitivity of 0.7, there were 3.8 FPs/image for the original CAD, 3.3 for the proposed technique, and 2.2 for the modified CAD using manual matching, a 12.6% and 42.1% reduction, respectively. At an FP rate of 1.0 per image, the sensitivities for the original CAD, the proposed technique and the modified CAD using manual matching were 0.47, 0.51 and 0.60, respectively. Preliminary results show that CAD with bilateral pairing did not achieve a significant FP-reduction.