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Reconstruction methods for combined HAADF-STEM and EDS tomography
The research in this thesis is focused on tomographic reconstruction based on two imaging modalities in electron microscopy. The first modality is high angle annular dark field scanning transmission microscopy (HAADF-STEM), and the second modality is energy-dispersive X-ray spectroscopy (EDS). In this Ph.D. thesis, we propose several approaches to pave the way for HAADF- STEM + EDS tomography: (1) the HAADF-EDS bimodal tomographic reconstruction technique, which is based on jointly modeling the consistency of the two imaging modalities; (2) TNV-regularized joined reconstruction which allows to incorporate the prior knowledge that common edges exist in the reconstructions from HAADF and EDS data respectively; (3) a set of algorithmic recipes to tailor various reconstruction algorithms for given experimental conditions and sample properties; (4) an algorithm for automatically correcting the nonlinear damping effects in HAADF-STEM tomographic data.
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Show moreThe research in this thesis is focused on tomographic reconstruction based on two imaging modalities in electron microscopy. The first modality is high angle annular dark field scanning transmission microscopy (HAADF-STEM), and the second modality is energy-dispersive X-ray spectroscopy (EDS). In this Ph.D. thesis, we propose several approaches to pave the way for HAADF- STEM + EDS tomography: (1) the HAADF-EDS bimodal tomographic reconstruction technique, which is based on jointly modeling the consistency of the two imaging modalities; (2) TNV-regularized joined reconstruction which allows to incorporate the prior knowledge that common edges exist in the reconstructions from HAADF and EDS data respectively; (3) a set of algorithmic recipes to tailor various reconstruction algorithms for given experimental conditions and sample properties; (4) an algorithm for automatically correcting the nonlinear damping effects in HAADF-STEM tomographic data.Show less- All authors
- Zhong, Z.
- Supervisor
- Batenburg, K.J.
- Co-supervisor
- Rieger, B.
- Committee
- Vaart, A.W. van der; Edixhoven, S.J.; Bals, S.; Verbeek, J.J.; Leeuwen, T. van
- Qualification
- Doctor (dr.)
- Awarding Institution
- Centrum Wiskunde & Informatica, Science, Leiden University
- Date
- 2018-12-10
- ISBN (print)
- 9789463234177