Anisotropic Nonlinear Filtering of Cellular Structures in Cryoelectron Tomography

Authors:
Jose-Jesus Fernandez;Sam Li
Affiliations:
University of Almeria, Spain;MRC Laboratory of Molecular Biology
Venue:
Computing in Science and Engineering
Year:
2005

Citing 3
Cited 5

Scale-Space and Edge Detection Using Anisotropic Diffusion

IEEE Transactions on Pattern Analysis and Machine Intelligence
Coherence-Enhancing Diffusion Filtering

International Journal of Computer Vision
Selection of Optimal Stopping Time for Nonlinear Diffusion Filtering

International Journal of Computer Vision

High performance noise reduction for biomedical multidimensional data

Digital Signal Processing
Efficient parallel implementation of iterative reconstruction algorithms for electron tomography

Journal of Parallel and Distributed Computing
Three-Dimensional Anisotropic Noise Reduction with Automated Parameter Tuning: Application to Electron Cryotomography

Current Topics in Artificial Intelligence
Three-dimensional feature-preserving noise reduction for real-time electron tomography

Digital Signal Processing
Evaluation of parallel paradigms on anisotropic nonlinear diffusion

Euro-Par'06 Proceedings of the 12th international conference on Parallel Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Cryo-electron tomography has emerged as a leading imaging technique in structural biology, with a unique potential for visualizing the molecular architecture of complex biological specimens. This technique ensures the best possible preservation of the biological material at expenses of producing extremely noisy three-dimensional density maps. A challenging computational task in this discipline is to increase the signal-to-noise ratio to allow their visualization and interpretation. This article describes an approach for denoising that is based on anisotropic nonlinear diffusion. The method combines structure-preserving noise reduction with a strategy to enhance local structures and a mechanism to further smooth the background. Furthermore, the authors have formulated a new criterion for stopping the iterative process. The performance of the approach is illustrated with its application to several complex biological specimens.