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Toward unsupervised single-shot diffractive imaging of heterogeneous particles using X-ray free-electron lasers

MPS-Authors
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Steinbrener,  Jan F.
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

/persons/resource/persons95345

Shoeman,  Robert L.
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

/persons/resource/persons94117

Lomb,  Lukas
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

/persons/resource/persons93693

Kassemeyer,  Stephan
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

/persons/resource/persons92822

Erk,  Benjamin
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

/persons/resource/persons117794

Rolles,  Daniel
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

/persons/resource/persons95029

Rudek,  Benedikt
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

/persons/resource/persons92933

Foucar,  Lutz
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

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Nass,  Karol
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

/persons/resource/persons95189

Schlichting,  Ilme
Department of Biomolecular Mechanisms, Max Planck Institute for Medical Research, Max Planck Society;

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Citation

Park, H. J., Loh, N. D., Sierra, R. G., Hampton, C. Y., Starodub, D., Martin, A. V., et al. (2013). Toward unsupervised single-shot diffractive imaging of heterogeneous particles using X-ray free-electron lasers. Optics Express, 21(23), 28729-28742. doi:10.1364/OE.21.028729.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0019-90E6-9
Abstract
Single shot diffraction imaging experiments via X-ray free-electron lasers can generate as many as hundreds of thousands of diffraction patterns of scattering objects. Recovering the real space contrast of a scattering object from these patterns currently requires a reconstruction process with user guidance in a number of steps, introducing severe bottlenecks in data processing. We present a series of measures that replace user guidance with algorithms that reconstruct contrasts in an unsupervised fashion. We demonstrate the feasibility of automating the reconstruction process by generating hundreds of contrasts obtained from soot particle diffraction experiments