Spatially-Adaptive Reconstruction in Computed Tomography Using Neural Networks

@article{Boublil2015SpatiallyAdaptiveRI,
  title={Spatially-Adaptive Reconstruction in Computed Tomography Using Neural Networks},
  author={David Boublil and Michael Elad and Joseph Shtok and Michael Zibulevsky},
  journal={IEEE Transactions on Medical Imaging},
  year={2015},
  volume={34},
  pages={1474-1485}
}
We propose a supervised machine learning approach for boosting existing signal and image recovery methods and demonstrate its efficacy on example of image reconstruction in computed tomography. Our technique is based on a local nonlinear fusion of several image estimates, all obtained by applying a chosen reconstruction algorithm with different values of its control parameters. Usually such output images have different bias/variance trade-off. The fusion of the images is performed by feed… CONTINUE READING
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References

Publications referenced by this paper.
SHOWING 1-10 OF 36 REFERENCES

Adaptive filtering for noise reduction in x-ray computed tomography

  • Anja Borsdorf
  • Ph.D. Thesis, .
  • 2009
1 Excerpt

A neural network approach for image reconstruction in electron magnetic resonance tomography

  • R. Murugesan DC Durairaj, MC Krishna
  • Comput. Biol. Med., vol. 37, no. 10, pp. 1492–501…
  • 2007
2 Excerpts

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