Three-dimensional feature-preserving noise reduction for real-time electron tomography

doi:10.1016/j.dsp.2009.12.010

Digital Signal Processing

Volume 20, Issue 4, July 2010, Pages 1162-1172

https://doi.org/10.1016/j.dsp.2009.12.010 Get rights and content

Abstract

Electron tomography (ET) is the leading imaging technique for visualizing the molecular architecture of complex biological specimens. Currently, real-time ET systems allow scientists to acquire experimental datasets with the electron microscope and obtain a preliminary version of the three-dimensional structure of the specimen. In principle, this rough structure allows assessment of the quality of the sample and can also be used as a guide to collect more datasets. However, in practice, the low signal-to-noise ratio of the ET datasets precludes detailed interpretation and makes their assessment difficult. Therefore, noise reduction methods must be integrated in these real-time ET systems for their fully exploitation. This work proposes and evaluates two different multithreaded implementations of a sophisticated noise reduction method with capabilities of preservation of biologically relevant features. The exploitation of the computing power of modern multicore platforms makes this noise reduction method provide datasets appropriate for assessment in a matter of a few minutes, thereby making it suitable for integration in current real-time electron tomography systems.

Section snippets

Jose-Jesus Fernández received the M.Sc. and Ph.D. degrees in computer science from the University of Granada, Spain, in 1992 and 1997, respectively. From 2002 to 2006 he was a postdoctoral scientist at the Laboratory of Molecular Biology (Medical Research Council, Cambridge, UK). In the last few years he was a professor of computer science at the University of Almeria, Almeria, Spain. In 2009 he got a position as a scientist at the National Center for Biotechnology (CNB) of the Spanish National

References (32)

S.Q. Zheng et al.
UCSF tomography: An integrated software suite for real-time electron microscopic tomographic data collection, alignment, and reconstruction
J. Struct. Biol.
(2007)
J.J. Fernandez
High performance computing in structural determination by electron cryomicroscopy
J. Struct. Biol.
(2008)
A.S. Frangakis et al.
Noise reduction in electron tomographic reconstructions using nonlinear anisotropic diffusion
J. Struct. Biol.
(2001)
J.J. Fernandez et al.
An improved algorithm for anisotropic nonlinear diffusion for denoising cryo-tomograms
J. Struct. Biol.
(2003)
S. Tabik et al.
High performance noise reduction for biomedical multidimensional data
Digital Signal Processing
(2007)
J. Briggs et al.
The mechanism of HIV-1 core assembly: Insights from 3D reconstructions of authentic virions
Structure
(2006)
J.R. Bilbao-Castro et al.
Exploiting desktop supercomputing for three-dimensional electron microscopy reconstructions using art with blobs
J. Struct. Biol.
(2009)
V. Lucic et al.
Structural studies by electron tomography: From cells to molecules
Annu. Rev. Biochem.
(2005)
J.J. Fernandez et al.
Image processing and 3D reconstruction in electron microscopy
IEEE Signal Process. Mag.
(2006)
A.P. Leis et al.
Cryo-electron tomography of biological specimens
IEEE Signal Process. Mag.
(2006)

O. Medalia et al.

Macromolecular architecture in eukaryotic cells visualized by cryoelectron tomography

Science

(2002)

K. Grunewald et al.

Three-dimensional structure of herpes simplex virus from cryo-electron tomography

Science

(2003)

M. Cyrklaff et al.

Cryo-electron tomography of vaccinia virus

Proc. Natl. Acad. Sci. USA

(2005)

D. Nicastro et al.

The molecular architecture of axonemes revealed by cryoelectron tomography

Science

(2006)

A. Al-Amoudi et al.

The molecular architecture of cadherins in native epidermal desmosomes

Nature

(2007)

R.H.M. Schoenmakers et al.

New software for high resolution, high throughput electron tomography

Micros. Anal.

(2005)

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Jose-Antonio Martínez received the M.Sc. and Ph.D. degrees in computer science from the University of Granada, Spain, in 1992 and from the University of Almeria, Spain, in 2007, respectively. He is an associate professor of computer science at the University of Almeria, Almeria, Spain. He has long expertise in parallel computing, computer architecture and networking. His current research interests include high performance computing paradigms, including message passing, multithreading, GPU computing and hybrid techniques for heterogeneous platforms, as well as applications for optimization and image processing.

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Three-dimensional feature-preserving noise reduction for real-time electron tomography

Abstract

Section snippets

J. Struct. Biol.

J. Struct. Biol.

J. Struct. Biol.

J. Struct. Biol.

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