Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5914785 | Journal of Structural Biology | 2011 | 9 Pages |
Abstract
Reference-based methods have dominated the approaches to the particle selection problem, proving fast, and accurate on even the most challenging micrographs. A reference volume, however, is not always available and compiling a set of reference projections from the micrographs themselves requires significant effort to attain the same level of accuracy. We propose a reference-free method to quickly extract particles from the micrograph. The method is augmented with a new semi-supervised machine-learning algorithm to accurately discriminate particles from contaminants and noise.
Related Topics
Life Sciences
Biochemistry, Genetics and Molecular Biology
Molecular Biology
Authors
Robert Langlois, Jesper Pallesen, Joachim Frank,