GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation.

@article{Jia2010GPUbasedFC,
  title={GPU-based fast cone beam CT reconstruction from undersampled and noisy projection data via total variation.},
  author={Xun Jia and Yifei Lou and Ruijiang Li and William Y. Song and Steve B. Jiang},
  journal={Medical physics},
  year={2010},
  volume={37 4},
  pages={1757-60}
}
PURPOSE Cone-beam CT (CBCT) plays an important role in image guided radiation therapy (IGRT). However, the large radiation dose from serial CBCT scans in most IGRT procedures raises a clinical concern, especially for pediatric patients who are essentially excluded from receiving IGRT for this reason. The goal of this work is to develop a fast GPU-based algorithm to reconstruct CBCT from undersampled and noisy projection data so as to lower the imaging dose. METHODS The CBCT is reconstructed… CONTINUE READING
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Development of a GPUbased Monte Carlo dose calculation code for coupled electronphoton trasport

  • J. Sempau, D. Choi, A. Majumdar, S. B. Jiang
  • 2010

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