Exact reduced-complexity maximum likelihood reconstruction of multiple 3-D objects from unlabeled unoriented 2-D projections and electron microscopy of viruses.

Exact reduced-complexity maximum likelihood reconstruction of multiple 3-D objects from unlabeled unoriented 2-D projections and electron microscopy of viruses. Research Abstract Details 

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Exact reduced-complexity maximum likelihood reconstruction of multiple 3-D objects from unlabeled unoriented 2-D projections and electron microscopy of viruses. Abstract Text:

Junghoon Lee,Peter C Doerschuk,John E Johnson,Junghoon Lee,Peter C Doerschuk,John E Johnson,

In cryo-electron microscopy, the data is comprised of noisy 2-D projection images of the 3-D electron scattering intensity of the object where the orientation of the projections is unknown. Often, the images show randomly selected objects from a mixture of different types of objects. Objects of different type may be unrelated, e.g., different species of virus, or related, e.g., different conformations of the same species of virus. Due to the low SNR and the 2-D nature of the data, it is challenging to determine the type of the object shown in an individual image. A statistical model and maximum likelihood estimator that computes simultaneous 3-D reconstruction and labels using an expectation maximization algorithm exists but requires extensive computation due to the numerical evaluation of 3-D or 5-D integrations of a square matrix of dimension equal to the number of degrees of freedom in the 3-D reconstruction. By exploiting the geometry of rotations in 3-D, the estimation problem can be transformed so that the inner-most numerical integral has a scalar rather than a matrix integrand. This leads to a dramatic reduction in computation, especially as the number of degrees of freedom in the 3-D reconstruction increases. Numerical examples of the 3-D reconstructions are provided based on synthetic and experimental images where the objects are small spherical viruses.

Exact reduced-complexity maximum likelihood reconstruction of multiple 3-D objects from unlabeled unoriented 2-D projections and electron microscopy of viruses. Publishing Authors By Initials

J Lee,PC Doerschuk,JE Johnson,J Lee,PC Doerschuk,JE Johnson,

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Exact reduced-complexity maximum likelihood reconstruction of multiple 3-D objects from unlabeled unoriented 2-D projections and electron microscopy of viruses. Journal Published:

PUBLICATION TYPE: Research Support, U.S. Gov't,

Journal: IEEE transactions on image processing : a publicat

VOLUME: 16

Page Numbers: 2865-78

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ISSN: 1057-7149

DAY: 20

MONTH: Dec

YEAR: 2007

Exact reduced-complexity maximum likelihood reconstruction of multiple 3-D objects from unlabeled unoriented 2-D projections and electron microscopy of viruses. Information

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LANGUAGE: eng

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Grant and Affiliation Information for Exact reduced-complexity maximum likelihood reconstruction of multiple 3-D objects from unlabeled unoriented 2-D projections and electron microscopy of viruses.

AFFILIATION: School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA. junghoon@purdue.edu

Country: United States

AGENCY: United States NIBIB

GRANT: 1R01EB000432-01

ACRONYM: EB

MEDLINETA: IEEE Trans Image Process

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