Display thresholding of images and observer detection performance.

In this experiment we studied how thresholding by the gray-scale display transformation altered the observer's ability to detect small, high-contrast lesions in both smooth (lower-noise) and sharp (higher-noise) reconstructions of computed tomographic (CT) images. Different display conditions manipulated the level setting of a narrow CT display window. This varied the fraction of thresholded pixels, set to the maximum or minimum values of brightness in relevant locations of the displayed images. Observers' ability to detect lesions in the smooth CT images was unaffected by moderate asymmetries in the display level but then abruptly declined at both the extremely high- and low-level settings. In sharp CT images, the lesion gradually decreased in detectability as the level setting became more asymmetric. These effects of the display manipulations were modeled by a realizable physical detector, whose decision variable was the cross correlation of the pixel display values with the lesion's expected profile at the specified (lesion and nonlesion) locations in the CT images. This cross-correlator model closely predicted the patterns of changes in lesion detectability that were measured for the human observers. It also predicted how thresholding of the higher or the lower CT numbers differentially altered the shapes of the observers' measured receiver-operating-characteristic curves for the smooth CT images.