Fast Gated PET Direct Motion Estimation Using Ordered Subsets

Alexandre Bousse, Brian F. Hutton, Kris Thielemans


Published in:Fully3D 2017 Proceedings


motion-compensated PET reconstruction, ordered subsets, maximum-likelihood, direct motion estimation
Direct motion compensation in gated PET can be achieved with maximum-likelihood (ML) joint activity reconstruction/motion estimation (JRM). Whereas the motion-compensated (MC) activity image can be efficiently updated with ordered subsets (OS) expectation maximisation (EM), the motion optimisation suffers from high computational cost due to the utilisation of line-search algorithms, which require to perform projections/backprojections each time the likelihood and its gradient are evaluated. The idea of this work is to use OS to speed-up the estimation of the motion parameters, by maximising each sub-likelihood sequentially. We show that the utilisation of OS significantly reduces the overall joint-estimation computational cost with negligible effect on the final solution.
Alexandre Bousse
University College London, United Kingdom
Brian F. Hutton
University College London, United Kingdom
Kris Thielemans
University College London, United Kingdom
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