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Orientation Determination of Cryo-EM Images Using Least Unsquared Deviations

Author(s): Wang, Lanhui; Singer, Amit; Wen, Zaiwen

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Abstract: A major challenge in single particle reconstruction from cryo-electron microscopy is to establish a reliable ab initio three-dimensional model using two-dimensional projection images with unknown orientations. Common-lines-based methods estimate the orientations without additional geometric information. However, such methods fail when the detection rate of common-lines is too low due to the high level of noise in the images. An approximation to the least squares global self-consistency error was obtained in [A. Singer and Y. Shkolnisky, SIAM J. Imaging Sci., 4 (2011), pp. 543-572] using convex relaxation by semidefinite programming. In this paper we introduce a more robust global self-consistency error and show that the corresponding optimization problem can be solved via semidefinite relaxation. In order to prevent artificial clustering of the estimated viewing directions, we further introduce a spectral norm term that is added as a constraint or as a regularization term to the relaxed minimization problem. The resulting problems are solved using either the alternating direction method of multipliers or an iteratively reweighted least squares procedure. Numerical experiments with both simulated and real images demonstrate that the proposed methods significantly reduce the orientation estimation error when the detection rate of common-lines is low.
Publication Date: 2013
Electronic Publication Date: 3-Dec-2013
Citation: Wang, Lanhui, Singer, Amit, Wen, Zaiwen. (2013). Orientation Determination of Cryo-EM Images Using Least Unsquared Deviations. SIAM JOURNAL ON IMAGING SCIENCES, 6 (2450 - 2483. doi:10.1137/130916436
DOI: doi:10.1137/130916436
ISSN: 1936-4954
Pages: 2450 - 2483
Type of Material: Journal Article
Version: Final published version. Article is made available in OAR by the publisher's permission or policy.

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