FIRT: Filtered iterative reconstruction technique with information restoration

Abstract

Electron tomography (ET) combining subsequent sub-volume averaging has been becoming a unique way to study the in situ 3D structures of macromolecular complexes. However, information missing in electron tomography due to limited angular sampling is still the bottleneck in high-resolution electron tomography application. Here, based on the understanding of smooth nature of biological specimen, we present a new iterative image reconstruction algorithm, FIRT (filtered iterative reconstruction technique) for electron tomography by combining the algebra reconstruction technique (ART) and the nonlinear diffusion (ND) filter technique. Using both simulated and experimental data, in comparison to ART and weight back projection method, we proved that FIRT could generate a better reconstruction with reduced ray artifacts and significant improved correlation with the ground truth and partially restore the information at the non-sampled angular region, which was proved by investigating the 90° re-projection and by the cross-validation method. This new algorithm will be subsequently useful in the future for both cellular and molecular ET with better quality and improved structural details.