Send to

Choose Destination
J Struct Biol. 2010 Sep;171(3):256-65. doi: 10.1016/j.jsb.2010.06.004. Epub 2010 Jun 9.

An adaptive Expectation-Maximization algorithm with GPU implementation for electron cryomicroscopy.

Author information

Department of Diagnostic Radiology, Yale University, New Haven, CT 06520, USA.


Maximum-likelihood (ML) estimation has very desirable properties for reconstructing 3D volumes from noisy cryo-EM images of single macromolecular particles. Current implementations of ML estimation make use of the Expectation-Maximization (EM) algorithm or its variants. However, the EM algorithm is notoriously computation-intensive, as it involves integrals over all orientations and positions for each particle image. We present a strategy to speedup the EM algorithm using domain reduction. Domain reduction uses a coarse grid to evaluate regions in the integration domain that contribute most to the integral. The integral is evaluated with a fine grid in these regions. In the simulations reported in this paper, domain reduction gives speedups which exceed a factor of 10 in early iterations and which exceed a factor of 60 in terminal iterations.

[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center