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Afanasyev P, Ravelli RB, Matadeen R, et al. A posteriori correction of camera characteristics from large image data sets. Sci Rep. 2015;5:10317doi: 10.1038/srep10317.
Afanasyev, P., Ravelli, R. B., Matadeen, R., De Carlo, S., van Duinen, G., Alewijnse, B., Peters, P. J., Abrahams, J. P., Portugal, R. V., Schatz, M., & van Heel, M. (2015). A posteriori correction of camera characteristics from large image data sets. Scientific reports, 510317. https://doi.org/10.1038/srep10317
Afanasyev, Pavel, et al. "A posteriori correction of camera characteristics from large image data sets." Scientific reports vol. 5 (2015): 10317. doi: https://doi.org/10.1038/srep10317
Afanasyev P, Ravelli RB, Matadeen R, De Carlo S, van Duinen G, Alewijnse B, Peters PJ, Abrahams JP, Portugal RV, Schatz M, van Heel M. A posteriori correction of camera characteristics from large image data sets. Sci Rep. 2015 Jun 11;5:10317. doi: 10.1038/srep10317. PMID: 26068909; PMCID: PMC4464200.
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Sci Rep. 2015 Jun 11;5:10317. doi: 10.1038/srep10317.

A posteriori correction of camera characteristics from large image data sets.

Scientific reports

Pavel Afanasyev, Raimond B G Ravelli, Rishi Matadeen, Sacha De Carlo, Gijs van Duinen, Bart Alewijnse, Peter J Peters, Jan-Pieter Abrahams, Rodrigo V Portugal, Michael Schatz, Marin van Heel

Affiliations

  1. 1] Leiden Institute of Chemistry, Leiden University, 2333 CC Leiden, The Netherlands [2] The Institute of Nanoscopy, Maastricht University, 6211 LK Maastricht, The Netherlands.
  2. The Institute of Nanoscopy, Maastricht University, 6211 LK Maastricht, The Netherlands.
  3. Netherlands Centre for Electron Nanoscopy (NeCEN), 2333 CC Leiden, The Netherlands.
  4. 1] Netherlands Centre for Electron Nanoscopy (NeCEN), 2333 CC Leiden, The Netherlands [2] FEI Company, 5651 GG Eindhoven, The Netherlands.
  5. FEI Company, 5651 GG Eindhoven, The Netherlands.
  6. Leiden Institute of Chemistry, Leiden University, 2333 CC Leiden, The Netherlands.
  7. Brazilian Nanotechnology National Laboratory - LNNano, CNPEM, C.P. 6192, 13083-970 Campinas SP, Brasil.
  8. Image Science Software GmbH, Gillweg 3, D-14193 Berlin, Germany.
  9. 1] Leiden Institute of Chemistry, Leiden University, 2333 CC Leiden, The Netherlands [2] Brazilian Nanotechnology National Laboratory - LNNano, CNPEM, C.P. 6192, 13083-970 Campinas SP, Brasil [3] Faculty of Natural Sciences, Imperial College London, London SW7 2AZ, UK.

PMID: 26068909 PMCID: PMC4464200 DOI: 10.1038/srep10317

Abstract

Large datasets are emerging in many fields of image processing including: electron microscopy, light microscopy, medical X-ray imaging, astronomy, etc. Novel computer-controlled instrumentation facilitates the collection of very large datasets containing thousands of individual digital images. In single-particle cryogenic electron microscopy ("cryo-EM"), for example, large datasets are required for achieving quasi-atomic resolution structures of biological complexes. Based on the collected data alone, large datasets allow us to precisely determine the statistical properties of the imaging sensor on a pixel-by-pixel basis, independent of any "a priori" normalization routinely applied to the raw image data during collection ("flat field correction"). Our straightforward "a posteriori" correction yields clean linear images as can be verified by Fourier Ring Correlation (FRC), illustrating the statistical independence of the corrected images over all spatial frequencies. The image sensor characteristics can also be measured continuously and used for correcting upcoming images.

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