2017McLeod Zorro

From 3DEM-Methods
Revision as of 13:44, 11 May 2017 by CoSS (talk | contribs) (Created page with "== Citation == McLeod, R. A.; Kowal, J.; Ringler, P. & Stahlberg, H. Robust image alignment for cryogenic transmission electron microscopy. Journal of structural biology, 201...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Citation

McLeod, R. A.; Kowal, J.; Ringler, P. & Stahlberg, H. Robust image alignment for cryogenic transmission electron microscopy. Journal of structural biology, 2017, 197, 279-293

Abstract

Cryo-electron microscopy recently experienced great improvements in structure resolution due to direct electron detectors with improved contrast and fast read-out leading to single electron counting. High frames rates enabled dose fractionation, where a long exposure is broken into a movie, permitting specimen drift to be registered and corrected. The typical approach for image registration, with high shot noise and low contrast, is multi-reference (MR) cross-correlation. Here we present the software package Zorro, which provides robust drift correction for dose fractionation by use of an intensity-normalized cross-correlation and logistic noise model to weight each cross-correlation in the MR model and filter each cross-correlation optimally. Frames are reliably registered by Zorro with low dose and defocus. Methods to evaluate performance are presented, by use of independently-evaluated even- and odd-frame stacks by trajectory comparison and Fourier ring correlation. Alignment of tiled sub-frames is also introduced, and demonstrated on an example dataset. Zorro source code is available at github.com/CINA/zorro.

Keywords

Links

http://www.sciencedirect.com/science/article/pii/S1047847716302520

Related software

Related methods

Comments