Noise Reduction in Electron Tomographic Reconstructions Using Nonlinear Anisotropic Diffusion

Noise Reduction in Electron Tomographic Reconstructions Using Nonlinear Anisotropic Diffusion Electrontomography is a powerful technique capable of giving unique insights into the three-dimensional structural organization of pleomorphic biological objects. However, visualization and interpretation of the resulting volumetric data are hampered by an extremely low signal-to-noise ratio, especially when ice-embedded biological specimens are investigated. Usually, isosurface representation or volume rendering of such data is hindered without any further signal enhancement. We propose a novel technique for noise reduction based on nonlinear anisotropic diffusion. The approach combines efficient noise reduction with excellent signal preservation and is clearly superior to conventional methods (e.g., low-pass and median filtering) and invariant wavelet transform filtering. The gain in the signal-to-noise ratio is verified and demonstrated by means of Fourier shell correlation. Improved visualization performance after processing the 3D images is demonstrated with two examples, tomographic reconstructions of chromatin and of a mitochondrion. Parameter settings and discretization stencils are presented in detail. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Structural Biology Elsevier

Noise Reduction in Electron Tomographic Reconstructions Using Nonlinear Anisotropic Diffusion

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Publisher
Elsevier
Copyright
Copyright © 2001 Elsevier Science (USA)
ISSN
1047-8477
eISSN
1095-8657
DOI
10.1006/jsbi.2001.4406
Publisher site
See Article on Publisher Site

Abstract

Electrontomography is a powerful technique capable of giving unique insights into the three-dimensional structural organization of pleomorphic biological objects. However, visualization and interpretation of the resulting volumetric data are hampered by an extremely low signal-to-noise ratio, especially when ice-embedded biological specimens are investigated. Usually, isosurface representation or volume rendering of such data is hindered without any further signal enhancement. We propose a novel technique for noise reduction based on nonlinear anisotropic diffusion. The approach combines efficient noise reduction with excellent signal preservation and is clearly superior to conventional methods (e.g., low-pass and median filtering) and invariant wavelet transform filtering. The gain in the signal-to-noise ratio is verified and demonstrated by means of Fourier shell correlation. Improved visualization performance after processing the 3D images is demonstrated with two examples, tomographic reconstructions of chromatin and of a mitochondrion. Parameter settings and discretization stencils are presented in detail.

Journal

Journal of Structural BiologyElsevier

Published: Sep 1, 2001

References

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