Developments in component-based normalization for 3D PET

Normalization in positron emission tomography (PET) is the process of ensur ing that all lines of response joining detectors in coincidence have the sa me effective sensitivity. In three dimensional (3D) PET, normalization is c omplicated by the presence of a large proportion of scattered coincidences, and by the fact that cameras operating in 3D mode encounter a very wide ra nge of count-rates. In this work a component-based normalization model is p resented which separates the normalization of true and scattered coincidenc es and accounts for variations in normalization effects with count-rate. Th e effects of the individual components in the model on reconstructed images are investigated, and it is shown that only a subset of these components h as a significant effect on reconstructed image quality.