Exemplar-based inpainting as a solution to the missing wedge problem in electron tomography

Patrick Trampert, Wu Wang, Delei Chen, Raimond B. G. Ravelli, Tim Dahmen*, Peter J. Peters, Christian Kubel, Philipp Slusallek

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

A new method for dealing with incomplete projection sets in electron tomography is proposed. The approach is inspired by exemplar-based inpainting techniques in image processing and heuristically generates data for missing projection directions. The method has been extended to work on three dimensional data. In general, electron tomography reconstructions suffer from elongation artifacts along the beam direction. These artifacts can be seen in the corresponding Fourier domain as a missing wedge. The new method synthetically generates projections for these missing directions with the help of a dictionary based approach that is able to convey both structure and texture at the same time. It constitutes a preprocessing step that can be combined with any tomographic reconstruction algorithm. The new algorithm was applied to phantom data, to a real electron tomography data set taken from a catalyst, as well as to a real dataset containing solely colloidal gold particles. Visually, the synthetic projections, reconstructions, and corresponding Fourier power spectra showed a decrease of the typical missing wedge artifacts. Quantitatively, the inpainting method is capable to reduce missing wedge artifacts and improves tomogram quality with respect to full width half maximum measurements. (C) 2018 Published by Elsevier B.V.
Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalUltramicroscopy
Volume191
DOIs
Publication statusPublished - 1 Aug 2018

Keywords

  • Missing wedge
  • Inpainting
  • Electron tomography
  • Tomographic reconstruction
  • Dictionary-based approaches
  • RECONSTRUCTION TECHNIQUE
  • AXIS TOMOGRAPHY
  • TILT
  • MICROTOMOGRAPHY
  • MICROSCOPY
  • SERIES
  • SIRT

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