Adaptive Sparsifying Transforms for Iterative Tomographic Reconstruction

@inproceedings{Pfister2014AdaptiveST,
  title={Adaptive Sparsifying Transforms for Iterative Tomographic Reconstruction},
  author={Luke Pfister and Yoram Bresler},
  year={2014}
}
A major challenge in computed tomography imaging is to obtain high-quality images from low-dose measurements. Key to this goal are computationally efficient reconstruction algorithms combined with detailed signal models. We show that the recently introduced adaptive sparsifying transform (AST) signal model provides superior reconstructions from low-dose data at significantly lower cost than competing dictionary learning methods. We further accelerate this technique for tomography by utilizing… CONTINUE READING
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