Filling the Missing Cone

  • Iterative refinement procedure

Abstract -+

Information is missing from three- dimensional electron microscopy density maps. This can be recovered by iterative refinement strategies.

More detail+-

The density maps generated by electron microscopy are not perfect. In general, they suffer from low signal to noise ratio, radiation damage and are modulated by contrast transfer function. There can be several other factors depending on the techniques used to generate the maps. In electron tomography, there is a missing wedge in Fourier space; similarly in 2D electron crystallography the missing cone causes problems. In single particle reconstruction, if some of the views in the micrographs are missing, the Fourier space will have missing data. The missing data in Fourier space would lead to imperfect densities in real space. An iterative algorithm that generates a support of the voxels with meaningful densities in each iteration and partially moves the real space volume to the support can be applied to fill in the missing information.