Paper
27 August 2010 Classification of cryo electron microscopy images, noisy tomographic images recorded with unknown projection directions, by simultaneously estimating reconstructions and application to an assembly mutant of Cowpea Chlorotic Mottle Virus and portals of the bacteriophage P22
Junghoon Lee, Yili Zheng, Zhye Yin, Peter C. Doerschuk, John E. Johnson
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Abstract
Cryo electron microscopy is frequently used on biological specimens that show a mixture of different types of object. Because the electron beam rapidly destroys the specimen, the beam current is minimized which leads to noisy images (SNR substantially less than 1) and only one projection image per object (with an unknown projection direction) is collected. For situations where the objects can reasonably be described as coming from a finite set of classes, an approach based on joint maximum likelihood estimation of the reconstruction of each class and then use of the reconstructions to label the class of each image is described and demonstrated on two challenging problems: an assembly mutant of Cowpea Chlorotic Mottle Virus and portals of the bacteriophage P22.
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Junghoon Lee, Yili Zheng, Zhye Yin, Peter C. Doerschuk, and John E. Johnson "Classification of cryo electron microscopy images, noisy tomographic images recorded with unknown projection directions, by simultaneously estimating reconstructions and application to an assembly mutant of Cowpea Chlorotic Mottle Virus and portals of the bacteriophage P22", Proc. SPIE 7800, Image Reconstruction from Incomplete Data VI, 78000R (27 August 2010); https://doi.org/10.1117/12.862066
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KEYWORDS
Particles

Expectation maximization algorithms

Contrast transfer function

Electron microscopy

Spherical lenses

Scattering

Image classification

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