Perception of temporally filtered X-ray fluoroscopy images

For noisy X-ray fluoroscopy image sequences we quantitatively evaluated ima ge quality after digital temporal filtering to reduce noise. Using an exper imental paradigm called a reference/test adaptive forced-choice method we c ompared detectability of stationary ion-contrast disks in filtered and unfi ltered, computer-generated image sequences. In the first experiment, a ion- pass first order recursive filter used in X-ray fluoroscopy was found to be much less effective at enhancing detectability than predicted from the red uction of display noise variance, a common measurement of filter effectiven ess. Detectability nas reasonably predicted by a nonprewhitening human-obse rver model (NPW-HVS) that included an independently determined human tempor al-contrast-sensitivity function. In another experiment, designed to test m odels over a range of temporal frequencies, ne used paired high-pass and lo ci-pass temporal filters that both reduced noise variance by 25%. The high- pass filter was artificially applied to the noise only and greatly improved detectability; while the low-pass filter had little effect. The human-obse rver model quantitatively described the measurements, but classical prewhit ening and nonprewhitening signal detectors did not, As compared to the nonp rewhitening, spatio-temporal matched filter, human-observer efficiency was low and variable at 2.1%, 2.9%, and 0.06% for 60 frames 60 unfiltered low-p ass and high-pass noise, respectively. As compared to this detector, humans were not very effective at combining information across frames, On the oth er hand, signal to noise ratios (SNR's) from the human-observer model were comparable to human performance, and efficiencies were reasonably constant at 40%, 52%, and 32%,respectively, We conclude that it is imperative to inc lude human-observer models and experiments in the analysis of noise-reducti on filtering of noisy image sequences, such as X-ray fluoroscopy.