3D signal reconstruction from noisy projection data for stochastic objects as a generalization of Gaussian mixture parameter estimation

Yili Zheng; Peter C. Doerschuk

doi:10.1117/12.862064

27 August 2010 3D signal reconstruction from noisy projection data for stochastic objects as a generalization of Gaussian mixture parameter estimation

Yili Zheng, Peter C. Doerschuk

Author Affiliations +

Proceedings Volume 7800, Image Reconstruction from Incomplete Data VI; 78000L (2010) https://doi.org/10.1117/12.862064
Event: SPIE Optical Engineering + Applications, 2010, San Diego, California, United States

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.

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Yili Zheng and Peter C. Doerschuk "3D signal reconstruction from noisy projection data for stochastic objects as a generalization of Gaussian mixture parameter estimation", Proc. SPIE 7800, Image Reconstruction from Incomplete Data VI, 78000L (27 August 2010); https://doi.org/10.1117/12.862064

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