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3-D reconstructions of nanometer-scale helical objects from cryo electron microscopy images

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3 Author(s)
Lee, S. ; Biomed. Eng. & Electr. & Comput. Eng., Cornell Univ., Ithaca, NY, USA ; Chen, Q. ; Doerschuk, P.C.

Statistical algorithms are described for 3-D signal reconstruction problems where the object has a helical symmetry with unknown symmetry parameters and the data is cryo electron micrographs of multiple identical instances of the object. Two object models are described: a Fourier-Bessel series model for a helical object and a spherical harmonics series model for a motif which is then replicated in an array to form a helical object where, in both cases, the unknown parameters are the coefficients in the series. The measured images are essentially noisy 2-D projections of the 3-D electron scattering intensity where the projection orientation is not known. A maximum likelihood estimator computed by an expectation-maximization algorithm is used in both cases to estimate the unknown parameters.

Published in:

Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on

Date of Conference:

June 28 2009-July 1 2009

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