The great amount of slices in volumetric data sets and limited time prevents human observers from exhaustively pointing their high resolution processing fovea to all regions in the images. Thus, many image-regions are processed with nonfoveal peripheral visual processing. Yet, most studies quantifying human detectability of signals in computer simulated textures and medical image backgrounds, have measured performance without consideration of the location of the signal in the observer's eye relative to the fovea (retinal eccentricity). Here, we measure human observer detectability of signals in CT images as a function of retinal eccentricity. A representative signal was extracted from a liver image and was added to healthy liver backgrounds at random positions. The retinal eccentricities of the signal were manipulated by varying the position of the point at which observers fixated with their eyes. Real-time video-based eye tracking was used to ensure steady fixation. High contrast fiduciary marks indicated the only possible location of the signal which was present in 50% of the images. Single CT slices were presented for 200 ms or 1 second. The observer was instructed to decide whether the image contained a signal (yes/no task). We probed 6 eccentricities with 420 decision trials per eccentricity. We found a large detectability degradation with retinal eccentricity with d' degrading by 50% at an eccentricity of 9 degrees for a 200 ms display time.
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