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Deriving Neural Network Architectures Using Precision Learning: Parallel-to-Fan Beam Conversion

  • Christopher SybenEmail author
  • Bernhard Stimpel
  • Jonathan Lommen
  • Tobias Würfl
  • Arnd Dörfler
  • Andreas Maier
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11269)

Abstract

In this paper, we derive a neural network architecture based on an analytical formulation of the parallel-to-fan beam conversion problem following the concept of precision learning. The network allows to learn the unknown operators in this conversion in a data-driven manner avoiding interpolation and potential loss of resolution. Integration of known operators results in a small number of trainable parameters that can be estimated from synthetic data only. The concept is evaluated in the context of Hybrid MRI/X-ray imaging where transformation of the parallel-beam MRI projections to fan-beam X-ray projections is required. The proposed method is compared to a traditional rebinning method. The results demonstrate that the proposed method is superior to ray-by-ray interpolation and is able to deliver sharper images using the same amount of parallel-beam input projections which is crucial for interventional applications. We believe that this approach forms a basis for further work uniting deep learning, signal processing, physics, and traditional pattern recognition.

Keywords

Machine learning Precision learning Hybrid MRI/X-ray imaging 

Notes

Acknowledgement

This work has been supported by the project P3-Stroke, an EIT Health innovation project. EIT Health is supported by EIT, a body of the European Union.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Christopher Syben
    • 1
    • 2
    Email author
  • Bernhard Stimpel
    • 1
    • 2
  • Jonathan Lommen
    • 1
    • 2
  • Tobias Würfl
    • 1
  • Arnd Dörfler
    • 2
  • Andreas Maier
    • 1
  1. 1.Pattern Recognition Lab, Department of Computer ScienceFriedrich-Alexander-Universität Erlangen-NürnbergErlangenGermany
  2. 2.Department of NeuroradiologyUniversitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-NürnbergErlangenGermany

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