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Related Concept Videos

X-ray Imaging01:24

X-ray Imaging

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German physicist Wilhelm Röntgen (1845–1923) was experimenting with electrical current when he discovered that a mysterious and invisible "ray" would pass through his flesh but leave an outline of his bones on a screen coated with a metal compound. In 1895, Röntgen made the first durable record of the internal parts of a living human: an "X-ray" image (as it came to be called) of his wife’s hand. Scientists worldwide quickly began their own experiments with...
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Real-time image-content-based beamline control for smart 4D X-ray imaging.

Matthias Vogelgesang1, Tomas Farago2, Thilo F Morgeneyer3

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A new architecture enables efficient, scalable workflows for high-speed X-ray experiments at synchrotron facilities. This system supports advanced imaging techniques like four-dimensional tomography and laminography for real-time data analysis.

Keywords:
controllaminographytomography

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Area of Science:

  • Synchrotron radiation science
  • Experimental physics
  • Materials science

Background:

  • Real-time processing of X-ray image data is crucial for high-speed experiments.
  • Current systems lack efficient and scalable workflow construction for complex experiments.
  • Advanced techniques like four-dimensional (4D) tomography and laminography require sophisticated control systems.

Purpose of the Study:

  • To introduce a novel architecture for constructing scalable experiment workflows.
  • To enable efficient management of data acquisition, processing, and device control.
  • To support advanced in situ, in vivo, and operando imaging experiments.

Main Methods:

  • Development of a high-level control system architecture.
  • Integration of specialized building blocks for experimental control.
  • Management of low-level data acquisition, processing, and device modifications.

Main Results:

  • The described system efficiently supports parameterized and image-based feedback-driven control.
  • It facilitates the entire workflow from data acquisition to storage of raw and processed data.
  • The architecture is suitable for both routine and prototypical experiments.

Conclusions:

  • The proposed architecture addresses the need for scalable and efficient experiment workflows at synchrotron facilities.
  • It enhances the capabilities for conducting advanced 4D imaging experiments.
  • This system facilitates smart, high-speed experimental design and execution.