A very popular software tools for analyzing functional Magnetic Resonance Imaging data is SPM by the Functional Imaging Laboratory at the Wellcome Department of Imaging Neuroscience. In order to enhance the signal-to-noise ratio it provides the possibility to smooth the data in a pre-processing step by a Gaussian filter. However, this comes at the cost of reducing the effective resolution, which is especially disturbing at high spatial resolutions. In a series of recent papers we have shown, that using a structural adaptive smoothing algorithm based on the Propagation-Separation method allows for signal detection while preserving the shape and spatial extent of the activation areas. Here, we provide our implementation of this algorithm as a toolbox for SPM.

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  1. Sprekels, J├╝rgen: Weierstrass Institute for Applied Analysis and Stochastics (WIAS) (1998)

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