Classical detection theory and the cryo-EM particle selection problem

J Struct Biol. Jan-Feb 2004;145(1-2):111-22. doi: 10.1016/j.jsb.2003.10.025.


Particle selection is an essential but tedious step in the determination of macromolecular structures by single particle reconstruction. This paper presents an automatic, multi-reference particle detection scheme that is based on the classical matched filter principle. It makes use of a pre-whitening filter to standardize the noise, a reduced representation of the references by means of principal component analysis, and a statistic for distinguishing particles from image artifacts. Standardizing the noise allows the noise-induced false-positive frequency to be estimated, and also allows the distribution of the discrimination statistic to be calculated a priori. The method is demonstrated with an annotated dataset of cryo-EM images.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Algorithms*
  • Animals
  • Cryoelectron Microscopy / methods*
  • Data Interpretation, Statistical
  • Electronic Data Processing / methods
  • Fourier Analysis
  • Hemocyanins / chemistry
  • Hemocyanins / ultrastructure
  • Image Enhancement / methods*
  • Image Processing, Computer-Assisted / methods*
  • Imaging, Three-Dimensional
  • Models, Molecular
  • Mollusca
  • Particle Size
  • Pattern Recognition, Automated
  • Principal Component Analysis
  • Rotation
  • Software Design
  • Statistical Distributions


  • Hemocyanins
  • keyhole-limpet hemocyanin