Denoising and compensation of the missing wedge in cryo electron tomography

International audienceIn this study, we have addressed two important issues in cryo electron tomography images: the lowsignal-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 theFourier domain. Therefore, the Fourier domain is separated into two regions: the known spectrum (KS) and theunknown spectrum, the latter having the shape of a missing wedge (see Figure). The proposed method tacklesboth issues jointly, by iteratively applying a denoising algorithm in order to fill up the MW, and proceeds asfollows:[1] Excitation step: Add noise into the MW[2] Denoising step: Apply a patch-based denoising algorithm[3] Repeat steps 1 and 2, by keeping KS constant through the iterationsThe excitation step is used to randomly initialize the coefficients of the MW, whereas the denoising step acts as aspatial regularization. The employed denoising algorithm, which exploits the self-similarity of the image, filtersout coefficient values which are dissimilar to KS, thereby keeping similar ones. By iterating these steps, we areable to diffuse the information contained in KS into the MW.An application example on experimental data can be seen on the Figure, which shows the data in both spectraland spatial domain. The data contains a spherical gold particle, deformed by MW induced artifacts: elongation ofthe object, side- and ray-artifacts. From the residue image it can be seen that noise and MW artifacts have beenreduced, while preserving the details of the image. Experiments are being performed to verify if particledetection and alignment are enhanced by using the method as a pre-processing step