Fast count-dependent digital filtering of nuclear medicine images: concise communication

The formulation of an "optimal" filter for improving the quality of digitally recorded nuclear medicine images is reported in this paper. The method forms a Metz filter for each image based upon the total number of counts in the image, which in turn determines the average noise level. The parameters of the filter were optimized for a set of simulated images using the minimization of the mean-square error as the criterion. The speed of the image formation results from the use of an array processor. In a study of localization receiver operating characteristics (LROC) using the Alderson liver phantom, a significant improvement in tumor localization was found in images filtered with this technique, compared with the original digital images and those filtered by the nine-point binomial smoothing algorithm. The technique has been found useful for the filtering of static and dynamic studies as well as the two-dimensional pre-reconstruction filtering of images from single photon emission computerized tomography.