Resampling 4D images using adaptive filtering

We present an adaptive filtering based methodology for resampling 3D time series images using an extension of the method presented by simultaneously reducing the artifacts due to image noise and resample the data on a finer grid along the time dimension. This provides a methodology for obtaining high quality image resampling without the disadvantages of staircase artifacts created by more common interpolation methods such as linear interpolation. We present qualitative results of the algorithm on a data set of 4D cardiac MRI. This is a useful approach for any situation where we have a data set of 4D images needing to be resampled.