Meeting the Computational Demands of Nuclear Medical Imaging using Commodity Clusters

Even though Positron Emission Tomography (PET) is a relatively young technique within Nuclear Medical Imaging, it has already reached a high level of acceptance. However, in order to fully exploit its capabilities, computational intensive transformations have to be applied to the raw data acquired from the scanners in order to reach a satisfying image quality. One way to provide the required computational power in a cost{eective and ecient way, is to use parallel processing based on commodity clusters