Technical Note: PYRO-NN: Python reconstruction operators in neural networks.

Journal: Medical physics
Published Date:

Abstract

PURPOSE: Recently, several attempts were conducted to transfer deep learning to medical image reconstruction. An increasingly number of publications follow the concept of embedding the computed tomography (CT) reconstruction as a known operator into a neural network. However, most of the approaches presented lack an efficient CT reconstruction framework fully integrated into deep learning environments. As a result, many approaches use workarounds for mathematically unambiguously solvable problems.

Authors

  • Christopher Syben
    Friedrich-Alexander-University Erlangen-Nuremberg, Germany.
  • Markus Michen
    Pattern Recognition Lab, Friedich-Alexander Universität Erlangen-Nürnberg, 91058, Erlangen, Germany.
  • Bernhard Stimpel
    Pattern Recognition Lab, Friedich-Alexander Universität Erlangen-Nürnberg, 91058, Erlangen, Germany.
  • Stephan Seitz
    Pattern Recognition Lab, Friedich-Alexander Universität Erlangen-Nürnberg, 91058, Erlangen, Germany.
  • Stefan Ploner
    Pattern Recognition Lab, Friedich-Alexander Universität Erlangen-Nürnberg, 91058, Erlangen, Germany.
  • Andreas K Maier