We evaluated our virtual dual-energy radiography technique based on a massive-training artificial neural network (MTANN) in the improvement of the conspicuity of nodules in chest radiographs. To do this, we used a validation test database consisting of 118 chest radiographs with pulmonary nodules and an independent test database consisting of 136 digitized screen-film chest radiographs with 136 solitary pulmonary nodules collected from 14 medical institutions. When our virtual dual-energy radiography technique was applied to non-training chest radiographs, ribs and clavicles in the chest radiographs were suppressed substantially while the visibility of nodules and lung vessels was maintained. Thus, our virtual dual-energy radiography technique by means of the MTANN could potentially improve radiologists’ detection accuracy of lung nodules on chest radiographs.