Spatial Smoothness and Image Analysis in Statistical Brain Mapping for functional Magnetic Resonance (fMRI) and Positron Emission Tomography (PET)

A considerable effort has been placed into developing image analysis for the spatial statistical tools for evaluating positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) data. The goal for these statistical brain mapping tools is to create a standardized pipe-line for the analysis. However, this pipeline has many factors that are interrelated, vary between sites, and are undergoing continued development. As an example of an interrelated process that varies between scanning sites and experiments is the image interpolation component in image registration used for movement correction. However, this alters the final results through a change in the spatial smoothness of the data. We review spatial smoothness and other overall analysis issues of fMRI and PET data in addition to illustrating this interrelated processing step in subvoxel image registration