Abstract
Fluoroscopic images are degraded by scattering of x-rays from within the patient and by veiling glare in the image intensifier. Both of these degradations are well described by a response function applied to either the scatter-free or primary intensity. The response function is variable, with dependence on such factors as patient thickness and imaging geometry. We describe an automated regularization technique for obtaining response function parameters with a minimal loss of signal. This method requires a high-transmission structured reference object to be interposed between the x-ray source and the subject. We estimate the parameters by minimizing residual correlations between the reference object and the computed subject density after a scatter-glare correction. We use simulated images to evaluate our method for both ideal and clinically realistic conditions. We find that the residual root-mean-square (rms) error ideally decreases with an increasing number of independent pixels (N) as (1/N)1/2. In simulated 256x256 angiograms mean normalized rms errors were reduced from 40% to 11% in noise-free images, and from 41% to 17% in noisy images, with a similar improvement in densitometric vessel cross-section measurements. These results demonstrate the validity of the method for simulated images and characterize its expected performance on clinical images.
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