Sensitivity of a partially learned model-based reconstruction algorithm

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We replace part of a model-based iterative algorithm with a convolutional neural network in order to improve the quality of tomography reconstructions. We analyse its robustness against uncertainties in the image and uncertainties in system settings. Results are presented for the application of photoacoustic tomography in a limited angle setup.
Original languageEnglish
Title of host publication89th Annual Meeting of the International Association of Applied Mathematics and Mechanics (GAMM)
Number of pages2
Publication statusPublished - 17 Dec 2018

Publication series

NameProceedings in Applied Mathematics and Mechanics
PublisherWiley-VCH Verlag
ISSN (Print)1617-7061


  • inverse problems
  • reconstruction
  • deep learning
  • algorithm


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