The "missing wedge" of a single tilt in electron tomography introduces severe artifacts into the reconstructed results. To reduce the "missing wedge" effect, a widely used method is "multiple-tilt reconstruction," which collects projections using multiple axes. However, as the number of tilt series increases, the computing and memory costs also rise. The degree of parallelism is limited by the sample thickness, and a large memory requirement cannot be met by most multicore computers. In our study, we present a new fully distributed multiple-tilt simultaneous iterative reconstruction technique (DM-SIRT). To improve the parallelism of the reconstruction process and reduce the memory requirements of each process, we formulate the multiple-tilt reconstruction as a consensus optimization problem and design a DM-SIRT algorithm. Experiments show that in addition to slightly better resolution, DM-SIRT can obtain a 13.9 × accelerated ratio compared with the full multiple-tilt reconstruction version. It also has a 97% decrease in memory overhead and is 16 times more scalable than the full reconstruction version.
Keywords: TxBR; consensus optimization; cryoelectron tomography; multiple-tilt reconstruction; parallel computing.