In this study, an automated scheme for detecting pulmonary nodules in PET/CT images has been proposed using combined detection and hybrid false-positive (FP) reduction techniques. The initial nodule candidates were detected separately from CT and PET images. FPs were then eliminated in the initial candidates by using support vector machine with characteristic values obtained from CT and PET images. In the experiment, we evaluated proposed method using 105 cases of PET/CT images that were obtained in the cancer-screening program. We evaluated true positive fraction (TPF) and FP/case. As a result, TPFs of CT and PET detections were 0.76 and 0.44, respectively. However, by integrating the both results, TPF was reached to 0.82 with 5.14 FPs/case. These results indicate that our method may be of practical use for the detection of pulmonary nodules using PET/CT images.