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Tomosaic: efficient acquisition and reconstruction of teravoxel tomography data using limited-size synchrotron X-ray beams.

Rafael VescoviMing DuVincent de AndradeWilliam ScullinDogˇa GürsoyChris Jacobsen
Published in: Journal of synchrotron radiation (2018)
X-rays offer high penetration with the potential for tomography of centimetre-sized specimens, but synchrotron beamlines often provide illumination that is only millimetres wide. Here an approach is demonstrated termed Tomosaic for tomographic imaging of large samples that extend beyond the illumination field of view of an X-ray imaging system. This includes software modules for image stitching and calibration, while making use of existing modules available in other packages for alignment and reconstruction. The approach is compatible with conventional beamline hardware, while providing a dose-efficient method of data acquisition. By using parallelization on a distributed computing system, it provides a solution for handling teravoxel-sized or larger datasets that cannot be processed on a single workstation in a reasonable time. Using experimental data, the package is shown to provide good quality three-dimensional reconstruction for centimetre-sized samples with sub-micrometre pixel size.
Keyphrases
  • high resolution
  • electronic health record
  • big data
  • data analysis
  • deep learning
  • magnetic resonance imaging
  • mass spectrometry
  • magnetic resonance
  • artificial intelligence
  • dual energy
  • single cell
  • human health