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@ARTICLE{Dora:607320,
      author       = {Dora, Johannes and Möddel, Martin and Flenner, Silja and
                      Reimers, Jan and Zeller-Plumhoff, Berit and Schroer,
                      Christian and Knopp, Tobias and Hagemann, Johannes},
      title        = {{M}odel-based autofocus for near-field phase retrieval},
      journal      = {Optics express},
      volume       = {33},
      number       = {4},
      issn         = {1094-4087},
      address      = {Washington, DC},
      publisher    = {Optica},
      reportid     = {PUBDB-2024-01831},
      pages        = {6641 - 6657},
      year         = {2025},
      abstract     = {The phase problem is a well known ill-posed reconstruction
                      problem of coherent lens-less microscopic imaging, where
                      only the intensities of a complex wave-field are measured by
                      the detector and the phase information is lost. For the
                      reconstruction of sharp images from holograms in a
                      near-field experimental setting, it is crucial to solve the
                      autofocus problem, i.e., to precisely estimate the Fresnel
                      number of the forward model. Otherwise, blurred out-of focus
                      images that also can contain artifacts are the result. In
                      general, a simple distance measurement at the experiment is
                      not sufficiently accurate, thus the fine-tuning of the
                      Fresnel number has to be done prior to the actual
                      reconstructions. This can be done manually or automatically
                      by an estimation algorithm. To automatize the process, as
                      needed, e.g., for in-situ/operando experiments, different
                      focus criteria have been widely studied in literature but
                      are subjected to certain restrictions. The methods often
                      rely on image analysis of the reconstructed image, making
                      them sensitive to image noise and also neglecting
                      algorithmic properties of the applied phase retrieval. In
                      this paper, we propose a novel criterion, based on a
                      model-matching approach, which improves autofocusing by also
                      taking the underlying reconstruction algorithm, the forward
                      model and the measured hologram into account. We derive a
                      common autofocusing framework, based on a recent
                      phase-retrieval approach and a downhill-simplex method for
                      the automatic optimization of the Fresnel number. We further
                      demonstrate the robustness of the framework on different
                      data sets obtained at the nano imaging endstation of P05 at
                      PETRA III (DESY, Hamburg) operated by Helmholtz-Zentrum
                      Hereon.},
      cin          = {FS-PETRA / Hereon},
      ddc          = {530},
      cid          = {I:(DE-H253)FS-PETRA-20140814 / I:(DE-H253)Hereon-20210428},
      pnm          = {623 - Data Management and Analysis (POF4-623) / 6G3 - PETRA
                      III (DESY) (POF4-6G3) / HIDSS-0002 - DASHH: Data Science in
                      Hamburg - Helmholtz Graduate School for the Structure of
                      Matter $(2019_IVF-HIDSS-0002)$ / SFB 986 Z02 - Multiskalige
                      Analyse von Strukturen und Prozessen mit
                      Synchrotronstrahlung und Neutronen (Z02) (221133217) / DFG
                      project G:(GEPRIS)192346071 - SFB 986: Maßgeschneiderte
                      Multiskalige Materialsysteme - M3 (192346071)},
      pid          = {G:(DE-HGF)POF4-623 / G:(DE-HGF)POF4-6G3 /
                      $G:(DE-HGF)2019_IVF-HIDSS-0002$ / G:(GEPRIS)221133217 /
                      G:(GEPRIS)192346071},
      experiment   = {EXP:(DE-H253)P-P05-20150101},
      typ          = {PUB:(DE-HGF)16},
      UT           = {WOS:001437185600001},
      doi          = {10.1364/OE.544573},
      url          = {https://bib-pubdb1.desy.de/record/607320},
}