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We describe a method for computing a continuous time estimate of tracer density using list-mode positron emission tomography data. The rate function in each voxel is modeled as an inhomogeneous Poisson process whose rate function can be represented using a cubic B-spline basis. The rate functions are estimated by maximizing the likelihood of the arrival times of detected photon pairs over the control vertices of the spline, modified by quadratic spatial and temporal smoothness penalties and a penalty term to enforce nonnegativity. Randoms rate functions are estimated by assuming independence between the spatial and temporal randoms distributions. Similarly, scatter rate functions are estimated by assuming spatiotemporal independence and that the temporal distribution of the scatter is proportional to the temporal distribution of the trues. A quantitative evaluation was performed using simulated data and the method is also demonstrated in a human study using 11C-raclopride.

Original publication




Journal article


IEEE Trans Med Imaging

Publication Date





396 - 404


Algorithms, Brain, Carbon Radioisotopes, Computer Simulation, Humans, Image Enhancement, Models, Statistical, Phantoms, Imaging, Poisson Distribution, Raclopride, Radiopharmaceuticals, Tissue Distribution, Tomography, Emission-Computed