CNR enhancement in the presence of multiple interfering processes using linear filters

Given several images of the same slice, a linear filter can produce an image in which the contrast-to-noise ratio (CNR) between pathological and normal tissues is greater than in any of the initial images. To distinguish the pathology from more than one tissue, the filter should optimize the set of CNRs between the pathology and each of the interfering tissues. We define the optimal filter as the one which provides the largest value for the minimum CNR in the set and show how it is selected from a field of only four possibilities. The filter is demonstrated with both experimental phantom studies and clinical cases. Filter performance is compared with that of other techniques for distinguishing a desired feature from more than one interfering process.