Estimating the spectrum in computed tomography via Kullback–Leibler divergence constrained optimization

@article{Ha2019EstimatingTS,
  title={Estimating the spectrum in computed tomography via Kullback–Leibler divergence constrained optimization},
  author={Wooseok Ha and Emil Y. Sidky and Rina Foygel Barber and Taly Gilat Schmidt and Xiaochuan Pan},
  journal={Medical Physics},
  year={2019},
  volume={46},
  pages={81–92}
}
PURPOSE We study the problem of spectrum estimation from transmission data of a known phantom. The goal is to reconstruct an x-ray spectrum that can accurately model the x-ray transmission curves and reflects a realistic shape of the typical energy spectra of the CT system. METHODS Spectrum estimation is posed as an optimization problem with x-ray spectrum as unknown variables, and a Kullback-Leibler (KL)-divergence constraint is employed to incorporate prior knowledge of the spectrum and… 

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