Expansion-maximization-compression algorithm with spherical harmonics for single particle imaging with x-ray lasers.
Identifieur interne : 001F27 ( Main/Merge ); précédent : 001F26; suivant : 001F28Expansion-maximization-compression algorithm with spherical harmonics for single particle imaging with x-ray lasers.
Auteurs : Julien Flamant [France] ; Nicolas Le Bihan [France] ; Andrew V. Martin [Australie] ; Jonathan H. Manton [Australie]Source :
- Physical review. E [ 2470-0053 ] ; 2016.
Abstract
In three-dimensional (3D) single particle imaging with x-ray free-electron lasers, particle orientation is not recorded during measurement but is instead recovered as a necessary step in the reconstruction of a 3D image from the diffraction data. Here we use harmonic analysis on the sphere to cleanly separate the angular and radial degrees of freedom of this problem, providing new opportunities to efficiently use data and computational resources. We develop the expansion-maximization-compression algorithm into a shell-by-shell approach and implement an angular bandwidth limit that can be gradually raised during the reconstruction. We study the minimum number of patterns and minimum rotation sampling required for a desired angular and radial resolution. These extensions provide new avenues to improve computational efficiency and speed of convergence, which are critically important considering the very large datasets expected from experiment.
DOI: 10.1103/PhysRevE.93.053302
PubMed: 27301000
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<front><div type="abstract" xml:lang="en">In three-dimensional (3D) single particle imaging with x-ray free-electron lasers, particle orientation is not recorded during measurement but is instead recovered as a necessary step in the reconstruction of a 3D image from the diffraction data. Here we use harmonic analysis on the sphere to cleanly separate the angular and radial degrees of freedom of this problem, providing new opportunities to efficiently use data and computational resources. We develop the expansion-maximization-compression algorithm into a shell-by-shell approach and implement an angular bandwidth limit that can be gradually raised during the reconstruction. We study the minimum number of patterns and minimum rotation sampling required for a desired angular and radial resolution. These extensions provide new avenues to improve computational efficiency and speed of convergence, which are critically important considering the very large datasets expected from experiment.</div>
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