Section: New Software and Platforms

MWR

Missing Wedge Restoration (MWR) and Noise Removal in 3D Cryo-Tomography

Keywords: Image analysis - Inverse problem - Cryo-electron microscopy - Monte-Carlo methods - Bayesian estimation

Functional Description: The Missing Wedge Restoration (MWR) software enables to reduce the high amount of noise and artifacts observed in 3D cellular cryo-tomograms, induced by the presence of a missing wedge (MW) in the spectral domain. MWR takes as input a 3D tomogram derived from limited-angle tomography, and gives as output a 3D denoised and artifact compensated volume. The artifact compensation is achieved by filling up the MW with meaningful information. A Minimum Mean Square Error (MMSE) estimator is computed by applying a dedicated Markov Chain Monte-Carlo (MCMC) sampling procedure based on the Metropolis-Hasting algorithm. MWR can be used to enhance visualization or as a pre-processing step for image analysis, including segmentation and classification of macromolecules.

• Participants: Emmanuel Moebel and Antonio Martinez

• Partners: Max Planck Institute Martinsried - Fondation Fourmentin-Guilbert

• Contact: Charles Kervrann

• Publication: A Monte Carlo framework for missing wedge restoration and noise removal in cryo-electron tomography

• URL: https://gitlab.inria.fr/serpico/mwr