Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose X-ray computed tomography

@article{Wang2006PenalizedWL,
  title={Penalized weighted least-squares approach to sinogram noise reduction and image reconstruction for low-dose X-ray computed tomography},
  author={Jing Wang and Tianfang Li and Hongbing Lu and Zhengrong Liang},
  journal={IEEE Transactions on Medical Imaging},
  year={2006},
  volume={25},
  pages={1272-1283}
}
Reconstructing low-dose X-ray computed tomography (CT) images is a noise problem. This work investigated a penalized weighted least-squares (PWLS) approach to address this problem in two dimensions, where the WLS considers first- and second-order noise moments and the penalty models signal spatial correlations. Three different implementations were studied for the PWLS minimization. One utilizes a Markov random field (MRF) Gibbs functional to consider spatial correlations among nearby detector… CONTINUE READING
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