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Proceedings Paper

3D signal reconstruction from noisy projection data for stochastic objects as a generalization of Gaussian mixture parameter estimation
Author(s): Yili Zheng; Peter C. Doerschuk
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Paper Abstract

A statistical estimation problem for determining 3-D reconstructions from a single 2-D projection image of each of multiple objects when the objects are heterogeneous is described. The method is based on a Gaussian mixture description of the heterogeneity and is motivated by cryo electron microscopy of biological objects.

Paper Details

Date Published: 27 August 2010
PDF: 8 pages
Proc. SPIE 7800, Image Reconstruction from Incomplete Data VI, 78000L (27 August 2010); doi: 10.1117/12.862064
Show Author Affiliations
Yili Zheng, Lawrence Berkeley National Lab. (United States)
Peter C. Doerschuk, Cornell Univ. (United States)

Published in SPIE Proceedings Vol. 7800:
Image Reconstruction from Incomplete Data VI
Philip J. Bones; Michael A. Fiddy; Rick P. Millane, Editor(s)

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