期刊
ULTRAMICROSCOPY
卷 113, 期 -, 页码 120-130出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ultramic.2011.11.004
关键词
Electron tomography; Compressive sensing; Total variation minimization; Reconstruction algorithm
类别
资金
- Flemish Fund for Scientific Research (FWO Vlaanderen) [G.0247.08, AL527]
- Embedded Systems Institute (ESI)
- FEI company
- Dutch Ministry of Economic Affairs under the BSIK
- Netherlands Fund for Scientific Research (NWO)
- European Union (Integrated Infrastructure Initiative) [262348]
The 3D reconstruction of a tilt series for electron tomography is mostly carried out using the weighted backprojection (WBP) algorithm or using one of the iterative algorithms such as the simultaneous iterative reconstruction technique (SIRT). However, it is known that these reconstruction algorithms cannot compensate for the missing wedge. Here, we apply a new reconstruction algorithm for electron tomography, which is based on compressive sensing. This is a field in image processing specialized in finding a sparse solution or a solution with a sparse gradient to a set of ill-posed linear equations. Therefore, it can be applied to electron tomography where the reconstructed objects often have a sparse gradient at the nanoscale. Using a combination of different simulated and experimental datasets, it is shown that missing wedge artefacts are reduced in the final reconstruction. Moreover, it seems that the reconstructed datasets have a higher fidelity and are easier to segment in comparison to reconstructions obtained by more conventional iterative algorithms. (C) 2011 Elsevier B.V. All rights reserved.
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