PVC of Brain Images based on MRI Segmentation

This correction is based on the assumption that white matter uptake is homogeneous. All brain pixels are classified as white matter (WM) or grey matter (GM) and sorted into respective segments. Based on these segments and the assumed PET resolution the spill-out from WM to GM can be estimated and subtracted. Similarly, the spill-out from GM to the surroundings can be estimated and compensated for. The result is a grey matter image with corrected activity values in all pixels. This method was introduced by Muller-Gartner et al. [4].
Given a brain PET and an anatomical MRI of a subject, the implementation in PMOD allows the user performing the segmentation and apply the Muller-Gartner PVC in a fully automated way.