Phase retrieval from crystalline diffraction averaged over several different unit cells

Joe P J Chen; Richard Kirian; Kenneth R. Beyerlein; Richard J. Bean; Henry N. Chapman; Philip J. Bones; Rick P. Millane

doi:10.1145/2683405.2683456

Phase retrieval from crystalline diffraction averaged over several different unit cells

Joe P J Chen, Richard Kirian, Kenneth R. Beyerlein, Richard J. Bean, Henry N. Chapman, Philip J. Bones, Rick P. Millane

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In protein nanocrystallography using x-ray lasers, diffraction is measured from an ensemble of very small crystals. The measured diffraction data can sometimes be processed to estimate the continuous Fourier transform intensity of the contents within the unit cell that makes up the crystals. However, in most cases the intensity data are averaged over a number of different kinds of unit cell that can occur in the ensemble. We investigate the properties of this problem and describe two algorithms to reconstruct the electron density of these unit cells from the averaged x-ray diffraction intensity data. The algorithms are evaluated by simulation.

Original language	English (US)
Title of host publication	Proceedings of IVCNZ 2014: The 29th International Conference on Image and Vision Computing New Zealand
Publisher	Association for Computing Machinery
Pages	202-206
Number of pages	5
Volume	19-21-November-2014
ISBN (Electronic)	9781450331845
DOIs	https://doi.org/10.1145/2683405.2683456
State	Published - Nov 19 2014
Externally published	Yes
Event	29th International Conference on Image and Vision Computing New Zealand, IVCNZ 2014 - Hamilton, New Zealand Duration: Nov 19 2014 → Nov 21 2014

Other

Other	29th International Conference on Image and Vision Computing New Zealand, IVCNZ 2014
Country/Territory	New Zealand
City	Hamilton
Period	11/19/14 → 11/21/14

Keywords

Crystallography
Image reconstruction
Iterative search algorithms
Nanocrystals
Phase retrieval
Symmetry
X-ray free-electron lasers

ASJC Scopus subject areas

Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software

Access to Document

10.1145/2683405.2683456

Cite this

Chen, J. P. J., Kirian, R., Beyerlein, K. R., Bean, R. J., Chapman, H. N., Bones, P. J., & Millane, R. P. (2014). Phase retrieval from crystalline diffraction averaged over several different unit cells. In Proceedings of IVCNZ 2014: The 29th International Conference on Image and Vision Computing New Zealand (Vol. 19-21-November-2014, pp. 202-206). Association for Computing Machinery. https://doi.org/10.1145/2683405.2683456

Phase retrieval from crystalline diffraction averaged over several different unit cells. / Chen, Joe P J; Kirian, Richard; Beyerlein, Kenneth R. et al.

Proceedings of IVCNZ 2014: The 29th International Conference on Image and Vision Computing New Zealand. Vol. 19-21-November-2014 Association for Computing Machinery, 2014. p. 202-206.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chen, JPJ, Kirian, R, Beyerlein, KR, Bean, RJ, Chapman, HN, Bones, PJ & Millane, RP 2014, Phase retrieval from crystalline diffraction averaged over several different unit cells. in Proceedings of IVCNZ 2014: The 29th International Conference on Image and Vision Computing New Zealand. vol. 19-21-November-2014, Association for Computing Machinery, pp. 202-206, 29th International Conference on Image and Vision Computing New Zealand, IVCNZ 2014, Hamilton, New Zealand, 11/19/14. https://doi.org/10.1145/2683405.2683456

Chen JPJ, Kirian R, Beyerlein KR, Bean RJ, Chapman HN, Bones PJ et al. Phase retrieval from crystalline diffraction averaged over several different unit cells. In Proceedings of IVCNZ 2014: The 29th International Conference on Image and Vision Computing New Zealand. Vol. 19-21-November-2014. Association for Computing Machinery. 2014. p. 202-206 doi: 10.1145/2683405.2683456

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title = "Phase retrieval from crystalline diffraction averaged over several different unit cells",

abstract = "In protein nanocrystallography using x-ray lasers, diffraction is measured from an ensemble of very small crystals. The measured diffraction data can sometimes be processed to estimate the continuous Fourier transform intensity of the contents within the unit cell that makes up the crystals. However, in most cases the intensity data are averaged over a number of different kinds of unit cell that can occur in the ensemble. We investigate the properties of this problem and describe two algorithms to reconstruct the electron density of these unit cells from the averaged x-ray diffraction intensity data. The algorithms are evaluated by simulation.",

keywords = "Crystallography, Image reconstruction, Iterative search algorithms, Nanocrystals, Phase retrieval, Symmetry, X-ray free-electron lasers",

author = "Chen, {Joe P J} and Richard Kirian and Beyerlein, {Kenneth R.} and Bean, {Richard J.} and Chapman, {Henry N.} and Bones, {Philip J.} and Millane, {Rick P.}",

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doi = "10.1145/2683405.2683456",

language = "English (US)",

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AU - Chen, Joe P J

AU - Kirian, Richard

AU - Beyerlein, Kenneth R.

AU - Bean, Richard J.

AU - Chapman, Henry N.

AU - Bones, Philip J.

AU - Millane, Rick P.

PY - 2014/11/19

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N2 - In protein nanocrystallography using x-ray lasers, diffraction is measured from an ensemble of very small crystals. The measured diffraction data can sometimes be processed to estimate the continuous Fourier transform intensity of the contents within the unit cell that makes up the crystals. However, in most cases the intensity data are averaged over a number of different kinds of unit cell that can occur in the ensemble. We investigate the properties of this problem and describe two algorithms to reconstruct the electron density of these unit cells from the averaged x-ray diffraction intensity data. The algorithms are evaluated by simulation.

AB - In protein nanocrystallography using x-ray lasers, diffraction is measured from an ensemble of very small crystals. The measured diffraction data can sometimes be processed to estimate the continuous Fourier transform intensity of the contents within the unit cell that makes up the crystals. However, in most cases the intensity data are averaged over a number of different kinds of unit cell that can occur in the ensemble. We investigate the properties of this problem and describe two algorithms to reconstruct the electron density of these unit cells from the averaged x-ray diffraction intensity data. The algorithms are evaluated by simulation.

KW - Crystallography

KW - Image reconstruction

KW - Iterative search algorithms

KW - Nanocrystals

KW - Phase retrieval

KW - Symmetry

KW - X-ray free-electron lasers

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BT - Proceedings of IVCNZ 2014: The 29th International Conference on Image and Vision Computing New Zealand

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Phase retrieval from crystalline diffraction averaged over several different unit cells

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Keywords

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