Image quality assessment and image fusion for electron tomography

Research output: ThesisDissertation (TU Delft)

22 Downloads (Pure)

Abstract

Electron tomography is a powerful tool in materials science to characterize nanostructures in three dimensions (3D). In scanning transmission electron microscopy (STEM), the sample under study is exposed to a focused electron beam and tilted to obtain twodimensional (2D) projections at different angles; many imaging modes are available such as high-angle annular dark-field (HAADF). In tomography, the collection of projections is called a tilt-series, from which we can reconstruct a 3D image that represents the sample. While HAADF tomography can clearly reveal the inner structure of the sample, it cannot directly provide compositional information. To better understand nanomaterials with more types of elements, spectral imaging techniques like energy dispersive X-ray spectroscopy (EDS) must be pursued. EDS tomography, however, is currently hampered by slow data acquisition, resulting in a small number of elemental maps with low signalto- noise ratio (SNR). Electron tomography, especially EDS tomography, is an ill-posed inverse problem whose solution is not stable and unique. Although advanced reconstruction techniques may yield a more accurate result by incorporating prior knowledge, they also involve fine-tuning parameters that highly influence the reconstruction quality. Furthermore, while great efforts have been dedicated to developing tomography techniques for image enhancement, directly combining reconstruction volumes at hand has still not been widely considered to the best of our knowledge.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • Rieger, B., Supervisor
Award date24 Jun 2020
DOIs
Publication statusPublished - 15 May 2020

Keywords

  • image quality assessment
  • multimodal image fusion
  • electron tomography
  • HAADF-STEM
  • X-ray spectroscopy
  • EDS
  • nanomaterials

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