Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection

Doǧa Gürsoy*, Young P. Hong, Kuan He, Karl Hujsak, Seunghwan Yoo, Si Chen, Yue Li, Mingyuan Ge, Lisa M. Miller, Yong S. Chu, Vincent De Andrade, Kai He, Oliver Cossairt, Aggelos K. Katsaggelos, Chris Jacobsen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

As x-ray and electron tomography is pushed further into the nanoscale, the limitations of rotation stages become more apparent, leading to challenges in the alignment of the acquired projection images. Here we present an approach for rapid post-acquisition alignment of these projections to obtain high quality three-dimensional images. Our approach is based on a joint estimation of alignment errors, and the object, using an iterative refinement procedure. With simulated data where we know the alignment error of each projection image, our approach shows a residual alignment error that is a factor of a thousand smaller, and it reaches the same error level in the reconstructed image in less than half the number of iterations. We then show its application to experimental data in x-ray and electron nanotomography.

Original languageEnglish (US)
Article number11818
JournalScientific reports
Volume7
Issue number1
DOIs
StatePublished - Dec 1 2017

ASJC Scopus subject areas

  • General

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