Keywords:
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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