Field of View Extension in Computed Tomography Using Deep Learning Prior

@article{Huang2020FieldOV,
  title={Field of View Extension in Computed Tomography Using Deep Learning Prior},
  author={Yixing Huang and Lei Gao and Alexander Preuhs and A. Maier},
  journal={ArXiv},
  year={2020},
  volume={abs/1911.01178}
}
In computed tomography (CT), data truncation is a common problem. Images reconstructed by the standard filtered back-projection algorithm from truncated data suffer from cupping artifacts inside the field-of-view (FOV), while anatomical structures are severely distorted or missing outside the FOV. Deep learning, particularly the U-Net, has been applied to extend the FOV as a post-processing method. Since image-to-image prediction neglects the data fidelity to measured projection data, incorrect… Expand
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