A Monte Carlo Framework for Denoising and Missing Wedge Reconstruction in Cryo-electron Tomography

  • E. MoebelEmail author
  • C. Kervrann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11075)


We propose a statistical method to address an important issue in cryo electron tomography image analysis: reduction of a high amount of noise and artifacts due to the presence of a missing wedge (MW) in the spectral domain. The method takes as an input a 3D tomogram derived from limited-angle tomography, and gives as an output a 3D denoised and artifact compensated tomogram. The artifact compensation is achieved by filling up the MW with meaningful information. The method can be used to enhance visualization or as a pre-processing step for image analysis, including segmentation and classification. Results are presented for both synthetic and experimental data.


Cryo electron tomography Patch-based denoising Missing wedge restoration Stochastic models Monte Carlo simulation 


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© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Inria Rennes - Bretagne Atlantique, Campus universitaire de BeaulieuRennes CedexFrance

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