Three-dimensional reconstruction of cellular structures by electron microscope tomography and parallel computing

Electron microscope tomography has emerged as the leading technique for structure determination of cellular components with a resolution of a few nanometers, opening up exciting perspectives for visualizing the molecular architecture of the cytoplasm. This work describes and analyzes the parallelization of tomographic reconstruction algorithms for their application in electron microscope tomography of cellular structures. Efficient iterative algorithms that are characterized by a fast convergence rate have been used to tackle the image reconstruction problem. The use of smooth basis functions provides the reconstruction algorithms with an implicit regularization mechanism, very appropriate for highly noisy conditions such as those present in high-resolution electron tomographic studies. Parallel computing techniques have been applied so as to face the computational requirements demanded by the reconstruction of large volumes. An efficient domain decomposition scheme has been devised that leads to a parallel approach with capabilities of interprocessor communication latency hiding. The combination of efficient iterative algorithms and parallel computing techniques have proved to be well suited for the reconstruction of large biological specimens in electron tomography, yielding solutions in reasonable computational times. This work concludes that parallel computing will be the key to afford high-resolution structure determination of cells, so that the location of molecular signatures in their native cellular context can be made a reality. (C) 2003 Elsevier Inc. All rights reserved.