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Statistical image reconstruction for hybrid fluorescence optical tomography and positron emission tomography

We have developed a hybrid system for imaging small animals using fluorescence optical tomography (FOT) and positron emission tomography (PET) simultaneously. This paper presents a statistical method for reconstructing spatial distribution of dual-labeled tracers from the combined PET and FOT data. We use the Poisson likelihood function for the PET data and Gaussian distribution for the FOT data. The log-posterior density function is maximized by an optimization transfer algorithm. Computer simulations show that the hybrid reconstruction using combined PET-FOT data can achieve a better bias versus standard deviation performance than reconstructions using either PET or FOT data alone.