This paper describes an automatic parameter optimization method for anisotropic diffusion filters used to de-noise 2D and 3D MR images. The filtering process is integrated into a closed-loop system where image improvement is monitored indirectly by comparing the characteristics of the suppressed noise with those of the assumed noise model at the optimal point. In order to verify the performance of this approach, experimental results obtained with this method are presented together with the results obtained by median and k-nearest neighbor filters.
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