Objective functions for tomographic reconstruction from randoms-precorrected PET scans

In PET, usually the data are precorrected for accidental coincidence (AC) events by real-time subtraction of the delayed window coincidences. Randoms subtraction compensates in mean for AC events but destroys the Poisson statistics. Furthermore, for transmission tomography the weighted least-squares (WLS) method leads to systematic biases, especially at low count rates. We propose a new "shifted" Poisson (SP) model for precorrected PET data,...