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@INPROCEEDINGS{Welker:491435,
      author       = {Welker, Simon and Peer, Tal and Chapman, Henry N. and
                      Gerkmann, Timo},
      title        = {{D}eep {I}terative {P}hase {R}etrieval for {P}tychography},
      address      = {Piscataway, NJ},
      publisher    = {IEEE},
      reportid     = {PUBDB-2023-00144},
      isbn         = {978-1-6654-0540-9},
      pages        = {1591-1595},
      year         = {2022},
      note         = {Literaturangaben;},
      comment      = {[Ebook] 2022 IEEE International Conference on Acoustics,
                      Speech, and Signal Processing : proceedings : 7-13 May 2022,
                      virtual (all paper presentations) : 22-27 May 2022, main
                      venue: Marina Bay Sands Expo $\&$ Convention Center,
                      Singapore, satellite venue: Shenzhen, China / sponsored by:
                      the Institute of Electrical and Electronics Engineers,
                      Signal Processing Society , Piscataway, NJ : IEEE, 2022,},
      booktitle     = {[Ebook] 2022 IEEE International
                       Conference on Acoustics, Speech, and
                       Signal Processing : proceedings : 7-13
                       May 2022, virtual (all paper
                       presentations) : 22-27 May 2022, main
                       venue: Marina Bay Sands Expo $\&$
                       Convention Center, Singapore, satellite
                       venue: Shenzhen, China / sponsored by:
                       the Institute of Electrical and
                       Electronics Engineers, Signal
                       Processing Society , Piscataway, NJ :
                       IEEE, 2022,},
      abstract     = {One of the most prominent challenges in the field of
                      diffractive imaging is the phase retrieval (PR) problem: In
                      order to reconstruct an object from its diffraction pattern,
                      the inverse Fourier transform must be computed. This is only
                      possible given the full complex-valued diffraction data,
                      i.e. magnitude and phase. However, in diffractive imaging,
                      generally only magnitudes can be directly measured while the
                      phase needs to be estimated. In this work we specifically
                      consider ptychography, a sub-field of diffractive imaging,
                      where objects arereconstructed from multiple overlapping
                      diffraction images. We pro- pose an augmentation of existing
                      iterative phase retrieval algorithms with a neural network
                      designed for refining the result of each iteration. For this
                      purpose we adapt and extend a recently proposed architecture
                      from the speech processing field. Evaluation results show
                      the proposed approach delivers improved convergence rates in
                      terms of both iteration count and algorithm runtime.},
      month         = {May},
      date          = {2022-05-23},
      organization  = {ICASSP 2022 - 2022 IEEE International
                       Conference on Acoustics, Speech and
                       Signal Processing , Singapore
                       (Singapore), 23 May 2022 - 27 May 2022},
      cin          = {FS-CFEL-1},
      cid          = {I:(DE-H253)FS-CFEL-1-20120731},
      pnm          = {633 - Life Sciences – Building Blocks of Life: Structure
                      and Function (POF4-633) / HIDSS-0002 - DASHH: Data Science
                      in Hamburg - Helmholtz Graduate School for the Structure of
                      Matter $(2019_IVF-HIDSS-0002)$ / Leibniz Preis - Leibiz
                      Programm 2015: Prof. Dr. Henry N. Chapman
                      (DFG-Leibniz-2015-Chapman)},
      pid          = {G:(DE-HGF)POF4-633 / $G:(DE-HGF)2019_IVF-HIDSS-0002$ /
                      G:(DE-H253)DFG-Leibniz-2015-Chapman},
      experiment   = {EXP:(DE-MLZ)NOSPEC-20140101},
      typ          = {PUB:(DE-HGF)8 / PUB:(DE-HGF)7},
      doi          = {10.1109/ICASSP43922.2022.9746811},
      url          = {https://bib-pubdb1.desy.de/record/491435},
}