Proposes TOF-decomp ADMM that splits fast- and slow-CTR log-likelihood terms under a constraint to balance contributions and enable improved contrast-noise trade-offs via early stopping in multi-kernel TOF-PET reconstruction.
Improving timing resolution of BGO for TOF-PET: a comparative analysis with and without deep learning ,
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Multi-Kernel TOF-PET Image Reconstruction Using ADMM
Proposes TOF-decomp ADMM that splits fast- and slow-CTR log-likelihood terms under a constraint to balance contributions and enable improved contrast-noise trade-offs via early stopping in multi-kernel TOF-PET reconstruction.