title: Wavelets filtering for classification of very noisy electron microscopic single particles images--application on structure determination of VP5-VP19C recombinant.
abstract: BACKGROUND
  Images of frozen hydrated [vitrified] virus particles were taken close-to-focus in an electron microscope containing structural signals at high spatial frequencies. These images had very low contrast due to the high levels of noise present in the image. The low contrast made particle selection, classification and orientation determination very difficult. The final purpose of the classification is to improve the signal-to-noise ratio of the particle representing the class, which is usually the average. In this paper, the proposed method is based on wavelet filtering and multi-resolution processing for the classification and reconstruction of this very noisy data. A multivariate statistical analysis (MSA) is used for this classification.
  
  
  RESULTS
  The MSA classification method is noise dependent. A set of 2600 projections from a 3D map of a herpes simplex virus--to which noise was added--was classified by MSA. The classification shows the power of wavelet filtering in enhancing the quality of class averages (used in 3D reconstruction) compared to Fourier band pass filtering. A 3D reconstruction of a recombinant virus (VP5-VP19C) is presented as an application of multi-resolution processing for classification and reconstruction.
  
  
  CONCLUSIONS
  The wavelet filtering and multi-resolution processing method proposed in this paper offers a new way for processing very noisy images obtained from electron cryo-microscopes. The multi-resolution and filtering improves the speed and accuracy of classification, which is vital for the 3D reconstruction of biological objects. The VP5-VP19C recombinant virus reconstruction presented here is an example, which demonstrates the power of this method. Without this processing, it is not possible to get the correct 3D map of this virus.
authors.affiliation: Department of Biomedical Technology, College of Applied Medical Sciences, King Saud University, P,O, Box, 10219, Riyadh 11433, Kingdom of Saudi Arabia. asaad64@yahoo.com
authors.forename: Ali Samir
authors.initials: AS
authors.lastname: Saad
mesh_terms: D036022:Capsid Proteins / Q000648:ultrastructure*; D003198:Computer Simulation; D005374:Filtration; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008854:Microscopy, Electron / Q000379:methods*; D011994:Recombinant Proteins / Q000145:classification / Q000648:ultrastructure; D014771:Virion / Q000145:classification / Q000648:ultrastructure
chemical_list: D036022:Capsid Proteins; D011994:Recombinant Proteins; C082563:VP19 protein, Human herpesvirus 1; C442523:VP5 protein, Herpes simplex virus type 1