A digital filtration technique for scatter-glare correction based on thickness estimation

In order to quantitate anatomical and physiological parameters such as vessel dimensions and volumetric blood flow, it is necessary to make corrections for scatter and veiling glare, which are the major sources of nonlinearities in videodensitometric digital subtraction angiography (DSA). A convolution filtering technique has been investigated to estimate scatter-glare distribution in DSA images without the need to sample the scatter-glare intensity for each patient. This technique utilizes exposure parameters and image gray levels to assign equivalent Lucite thickness for every pixel in the image. The thickness information is then used to estimate scatter-glare intensity on a pixel-by-pixel basis. To test its ability to estimate scatter-glare intensity, the correction technique was applied to images of a Lucite step phantom, anthropomorphic chest phantom, head phantom, and animal models at different thicknesses, projections, and beam energies. The root-mean-square (rms) percentage error of these estimates was obtained by comparison with direct scatter-glare measurements made behind a lead strip. The average rms percentage errors in the scatter-glare estimate for the 25 phantom studies and the 17 animal studies were 6.44% and 7.96%, respectively. These results indicate that the scatter-glare intensity can be estimated with adequate accuracy for a wide range of thicknesses, projections, and beam energies using exposure parameters and gray level information