An expectation–maximization algorithm for positron emission particle tracking

We develop a new algorithm for the tracking of radioactive particles using Positron Emission Particle Tracking (PEPT). The relies on maximization likelihood simple Gaussian mixture model lines response associated with positron annihilation. includes component that accounts spurious caused by scattering and random coincidence, it treats relative activity as well their positions parameters to be inferred. Values these approximately maximize are computed application an expectation–maximization algorithm. A generalization particle velocities accelerations additional takes advantage information contained in exact timing annihilations reconstruct pieces trajectories rather than fixed positions, clear benefits. test both simulated experimental data. results show highly effective simultaneous many (up 80 one test). It provides estimates easily mapped entire handles variable number field view. ability track large robustly offers possibility dramatic expansion scope PEPT.