Nonlinear anisotropic diffusion in three-dimensional electron microscopy

Electron tomography is a powerful tool for investigating the three-dimensional (3D) structure of biological objects at a resolution in the nanometer range. However, visualization and interpretation of the resulting volumetric data is a very difficult task due to the extremely low signal to noise ratio (<0dB). In this paper, an approach for noise reduction in volumetric data is presented, based on nonlinear anisotropic diffusion, using a hybrid of the edge enhancing and the coherence enhancing techniques. When applied to both, artificial or real data sets, the method turns out to be superior to conventional filters. In order to assess noise reduction and structure preservation experimentally, resolution tests commonly used in structure analysis are applied to the data in the frequency domain.