A review of automatic particle recognition in Cryo-EM images / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1178-1182, 2010.
Article
in Chinese
| WPRIM
| ID: wpr-260914
ABSTRACT
Advances in cryo-electron microscopy (Cryo-EM) and single-particle reconstruction have led to increasingly high resolutions of macromolecular three-dimensional reconstruction. However, for keeping up the continuing improvements in resolution, it is necessary to increase the number of particles included in performing reconstructions. Manual selection of particles, even assisted by computer, is a bottleneck of single-particle reconstruction. Cryo-EM image has low signal-to-noise ratio and low contrast, which leads to difficulty in particle picking. Various approaches have been developed to address the problem of automatic particle. This paper describes the application of template-based method, edge based method, feature-based method, neural network, DoG-based and simulated annealing approach in particle picking. The characteristics of various approaches are discussed, and the future development is presented.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Particle Size
/
Ribosomes
/
Image Processing, Computer-Assisted
/
Electronic Data Processing
/
Chemistry
/
Cryoelectron Microscopy
/
Imaging, Three-Dimensional
/
Macromolecular Substances
/
Methods
/
Molecular Conformation
Limits:
Animals
/
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2010
Type:
Article
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