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Automatic Particle Picking From Electron Micrographs

Published online by Cambridge University Press:  14 March 2018

K. Ramani Lata ,
P. Penczek  and
J. Frank
K. Ramani Lata
Affiliation:
New York State Department of Health, Albany, NY
P. Penczek
Affiliation:
New York State Department of Health, Albany, NY
J. Frank
Affiliation:
New York State Department of Health, Albany, NY

Extract

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The present-day interactive manual selection of biological molecules from digitized micrographs for single particle averaging and reconstruction requires substantial effort and time. Thus a computer algorithm capable of recognition of structural content and selection of particles would be desirable. A few approaches have been proposed in the past. The method by Frank and Wagenknecht is based on the principle of correlation search. Van Heel's method is based on the computation of the local variance over a small area around each point of the image field. The method by Harauz and Fong- Lochovsky is based on edge-detection.

Type
Research Article
Information
Microscopy Today , Volume 3 , Issue 3 , April 1995 , pp. 12 - 13
Copyright
Copyright © Microscopy Society of America 1995

References

1. Frank, J. and Wagenknecht, T., Ultramicroscopy. 12(1984)169.CrossRefGoogle Scholar
2. van Heel, M., Ultramicroscopy. 8(1982)331.CrossRefGoogle Scholar
3. Harauz, G. and Fong-Lochovsky, A., Ultramicroscopy. 31 (1989) 333.CrossRefGoogle Scholar
4. Rademacher, M., J. Electron Microsc. Tech. 9(1988)359.CrossRefGoogle Scholar
5. Penczek, P., Grassucci, R.A. and Frank, J., Ultramicroscopy. (1394, in press).Google Scholar
6.Supported, in part, by grant NIH 1R01SM29169 (to J.F.)Google Scholar