Low-dose cryo electron ptychography via non-convex Bayesian optimization
Pelz PM, Qiu WX, Buecker R, Kassier G, Miller RJD (2017)
Publication Type: Journal article
Publication year: 2017
Journal
Book Volume: 7
Article Number: 9883
Journal Issue: 1
DOI: 10.1038/s41598-017-07488-y
Abstract
Electron ptychography has seen a recent surge of interest for phase sensitive imaging at atomic or near-atomic resolution. However, applications are so far mainly limited to radiation-hard samples, because the required doses are too high for imaging biological samples at high resolution. We propose the use of non-convex Bayesian optimization to overcome this problem, and show via numerical simulations that the dose required for successful reconstruction can be reduced by two orders of magnitude compared to previous experiments. As an important application we suggest to use this method for imaging single biological macromolecules at cryogenic temperatures and demonstrate 2D single-particle reconstructions from simulated data with a resolution up to 5.4 Å at a dose of 20e - /Å2. When averaging over only 30 low-dose datasets, a 2D resolution around 3.5 Å is possible for macromolecular complexes even below 100 kDa. With its independence from the microscope transfer function, direct recovery of phase contrast, and better scaling of signal-to-noise ratio, low-dose cryo electron ptychography may become a promising alternative to Zernike phase-contrast microscopy.
Authors with CRIS profile
Involved external institutions
Max-Planck-Instituts für Struktur und Dynamik der Materie (MPSD) / Max Planck Institute for the Structure and Dynamics of Matter
Germany (DE)
University of Toronto
Canada (CA)
Germany (DE)
University of Toronto
Canada (CA)
How to cite
APA:
Pelz, P.M., Qiu, W.X., Buecker, R., Kassier, G., & Miller, R.J.D. (2017). Low-dose cryo electron ptychography via non-convex Bayesian optimization. Scientific Reports, 7(1). https://dx.doi.org/10.1038/s41598-017-07488-y
MLA:
Pelz, Philipp Michael, et al. "Low-dose cryo electron ptychography via non-convex Bayesian optimization." Scientific Reports 7.1 (2017).
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