A globally convergent regularized ordered-subset algorithm for list-mode reconstruction

@article{Khurd2003AGC,
  title={A globally convergent regularized ordered-subset algorithm for list-mode reconstruction},
  author={Parmeshwar Khurd and Gene Gindi},
  journal={2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515)},
  year={2003},
  volume={5},
  pages={3057-3061 Vol.5}
}
List-mode (LM) acquisition allows collection of data attributes at higher levels of precision than is possible with binned (i.e. histogram-mode) data. Hence it is particularly attractive for low-count data in emission tomography. A LM likelihood and convergent EM algorithm for LM reconstruction was presented in (Parra et al., TMI, v17, 1998). Faster ordered subset (OS) reconstruction algorithms for LM 3-D PET were presented in (Reader et al., Phys. Med. Bio., v43, 1998). However, these OS… CONTINUE READING

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