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Proceedings Paper

3D macromolecule structure reconstruction from electron micrograph by exploiting symmetry and sparsity
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Paper Abstract

Single particle reconstruction is often employed for 3-D reconstruction of diverse macromolecules. However, the algorithm requires a good initial guess from a priori information to guarantee the convergence to the correct solution. This paper describes a novel model free 3-D reconstruction algorithm by employing the symmetry and sparsity of unknown structure. Especially, we develop an accurate and fully automatic iterative algorithm for 3D reconstruction of unknown helix structures. Because the macromolecule structure assumes only sparse supports in real space and the helical symmetry provides several symmetric views from a single micrograph, a reasonably quality 3-D reconstruction can be obtained from the limited views using the compressed sensing theory. Furthermore, the correct helix parameters usually provide the maximal variance of the reconstructed volume, facilitating the parameter estimation. Remarkably, the search space of helix parameter can be drastically reduced by exploiting the diffraction pattern. With the estimated helix parameter and additional 3-D registration, the multiple helix segments can be combined for the optimal quality reconstruction. Experimental results using synthetic and real helix data confirm that our algorithm provides superior reconstruction of 3-D helical structure.

Paper Details

Date Published: 26 February 2008
PDF: 8 pages
Proc. SPIE 6814, Computational Imaging VI, 68140X (26 February 2008); doi: 10.1117/12.766967
Show Author Affiliations
Min Woo Kim, Korea Advanced Institute of Science and Technology (South Korea)
Jiyoung Choi, Korea Advanced Institute of Science and Technology (South Korea)
Jong Chul Ye, Korea Advanced Institute of Science and Technology (South Korea)

Published in SPIE Proceedings Vol. 6814:
Computational Imaging VI
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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