A problem in most current computer-aided diagnostic (CAD) scheme is the relatively large number of false positives that are incorrectly reported as nodules by the scheme. Therefore, in this study, we developed a multiple-templates matching technique to significantly reduce the number of false positives in our CAD scheme. With this technique applied to our CAD scheme for detection of pulmonary nodules in chest radiographs, we removed a large number of false positives (44.3%) with reduction of a small number of true positives (2.3%). We believe that this technique has the potential to significantly improve the performance of many different CAD schemes for detection of various lesions in medical images including nodules in chest radiographs, masses and microcalcifications in mammograms, nodules, colon polyps, liver tumors, and aneurysms in CT images.