Three-Dimensional Anisotropic Noise Reduction with Automated Parameter Tuning: Application to Electron Cryotomography

  • J. J. Fernández
  • S. Li
  • V. Lucic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4788)

Abstract

This article presents an approach for noise filtering that is based on anisotropic nonlinear diffusion. The method combines edge-preserving noise reduction with a strategy to enhance local structures and a mechanism to further smooth the background. We have provided the method with an automatic mechanism for parameter self-tuning and for stopping the iterative filtering process. The performance of the approach is illustrated with its application to electron cryotomography (cryoET). CryoET has emerged as a leading imaging technique for visualizing the molecular architecture of complex biological specimens. A challenging computational task in this discipline is to increase the extremely low signal-to-noise ratio (SNR) to allow visualization and interpretation of the three-dimensional structures. The filtering method here proposed succeeds in substantially reducing the noise with excellent preservation of the structures.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • J. J. Fernández
    • 1
    • 2
  • S. Li
    • 1
  • V. Lucic
    • 3
  1. 1.MRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 2QHUK
  2. 2.Dept. Computer Architecture, University of Almería, Almería 04120Spain
  3. 3.Dept. Structural Biology, Max Planck Institute of Biochemistry, MartinsriedGermany

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