Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms.

@article{Tang2009PerformanceCB,
  title={Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms.},
  author={Jie Tang and Brian Nett and Guang-Hong Chen},
  journal={Physics in medicine and biology},
  year={2009},
  volume={54 19},
  pages={5781-804}
}
Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they enable accurate physical noise modeling. The newly developed compressive sampling/compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. The CS algorithm can be implemented in the statistical reconstruction framework as well. In this study, we compared the performance of two standard statistical… CONTINUE READING

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