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Section: New Results
Denoising and compensation of the missing wedge in cryo electron tomography
Participants : Emmanuel Moebel, Charles Kervrann.
In this study, we have addressed two important issues in cryo electron tomography (CET) images: the low signal-to-noise ratio and the presence of a missing wedge (MW) of information in the spectral domain. Indeed, according to the Fourier slice theorem, limited angle tomography results into an incomplete sampling of the Fourier domain. Therefore, the Fourier domain is separated into two regions: the known spectrum (KS) and the unknown spectrum, the latter having the shape of a missing wedge (see Fig. 13 ). The proposed method tackles both issues jointly, by iteratively applying a denoising algorithm in order to fill up the MW, and proceeds as follows:
The excitation step is used to randomly initialize the coefficients of the MW, whereas the denoising step acts as a spatial regularization. The employed denoising algorithm, which exploits the self-similarity of the image, filters out coefficient values which are dissimilar to KS, thereby keeping similar ones. By iterating these steps, we are able to diffuse the information contained in KS into the MW.
An application example on experimental data can be seen on Fig. 13 , which shows the data in both spectral and spatial domain. The data contains a spherical gold particle, deformed by MW induced artifacts: elongation of the object, side- and ray-artifacts. From the residue image it can be seen that noise and MW artifacts have been reduced, while preserving the details of the image. Experiments are being performed to verify if particle detection and alignment are enhanced by using the method as a pre-processing step.
Collaborators: Damien Larivière (Fondation Fourmentin-Guilbert),
Julio Ortiz (Max-Planck Institute, Martinsried, Germany).
