Using free-response methodology, we measured the comparative performance of trained observers for the task of detecting simulated pulmonary nodules in computed radiographic chest images that were compressed using the full-frame discrete cosine transform algorithm. six observers read fifty-one images containing a total of 372 simulated lesions of size ranging from 8 mm to 12 mm and with six different contrasts. The images were compressed to an average of 15:1 with the same parameters that were used in an earlier two-alternative forced-choice analysis. The results showed this level of compression did not increase the number of false-positive calls per image. also, observers tended to ignore the lowest contrast nodules in all images. At low contrast we expect compression to have the greatest effect. Therefore, overall performance was not degraded by the compression process, although performance was compromised at very low contrast.