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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/14816

Title: Wavelets filtering for classification of very noisy electron microscopic single particles images
Authors: Ali Saad Ph.D.
Keywords: hydrated , signal-to-noise ratio , spatial frequencies , wavelet filtering
Issue Date: 2003
Publisher: BMC Structural Biology
Abstract: 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.
URI: http://hdl.handle.net/123456789/14816
Appears in Collections:College of Applied Medical Sciences

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