We present the application of a novel nonparametric approach to restoration and interpolation of medical images. The proposed approach is based on the notion of spatially adaptive filtering where locally computed filters adjust to the underlying estimated geometry of the signal of interest. In particular, the approach allows for high performance denoising, restoration and interpolation of images from a variety of modalities using the same mathematical and computational framework.