• Corpus ID: 246240612

RISING a new framework for few-view tomographic image reconstruction with deep learning

@article{Evangelista2022RISINGAN,
  title={RISING a new framework for few-view tomographic image reconstruction with deep learning},
  author={David Evangelista and Elena Morotti and Elena Loli Piccolomini},
  journal={ArXiv},
  year={2022},
  volume={abs/2201.09777}
}
This paper proposes a new two-step procedure for sparse-view tomographic image reconstruction. It is called RISING, since it combines an early-stopped Rapid Iterative Solver with a subsequent Iteration Network-based Gaining step. So far, regularized iterative methods have widely been used for X-ray computed tomography image reconstruction from low-sampled data, since they converge to a sparse solution in a suitable domain, as upheld by the Compressed Sensing theory. Unfortunately, their use is…