English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Robust membrane detection based on tensor voting for electron tomography

Martinez-Sanchez, A., Garcia, I., Asano, S., Lucic, V., & Fernandez, J.-J. (2014). Robust membrane detection based on tensor voting for electron tomography. JOURNAL OF STRUCTURAL BIOLOGY, 186(1), 49-61. doi:10.1016/j.jsb.2014.02.015.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0019-8B79-4 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0019-8B7A-2
Genre: Journal Article

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Martinez-Sanchez, Antonio1, Author
Garcia, Inmaculada1, Author
Asano, Shoh2, Author              
Lucic, Vladan2, Author              
Fernandez, Jose-Jesus1, Author
Affiliations:
1external, ou_persistent22              
2Baumeister, Wolfgang / Molecular Structural Biology, Max Planck Institute of Biochemistry, Max Planck Society, ou_1565142              

Content

show
hide
Free keywords: CRYOELECTRON TOMOGRAPHY; OUTER-MEMBRANE; STEERABLE FILTERS; NOISE-REDUCTION; SEGMENTATION; RECONSTRUCTIONS; 3D; MICROTUBULES; DIFFUSIONSegmentation; Image processing; Electron tomography; Membrane; Tensor voting; Steerable filters;
 Abstract: Electron tomography enables three-dimensional (3D) visualization and analysis of the subcellular architecture at a resolution of a few nanometers. Segmentation of structural components present in 3D images (tomograms) is often necessary for their interpretation. However, it is severely hampered by a number of factors that are inherent to electron tomography (e.g. noise, low contrast, distortion). Thus, there is a need for new and improved computational methods to facilitate this challenging task. In this work, we present a new method for membrane segmentation that is based on anisotropic propagation of the local structural information using the tensor voting algorithm. The local structure at each voxel is then refined according to the information received from other voxels. Because voxels belonging to the same membrane have coherent structural information, the underlying global structure is strengthened. In this way, local information is easily integrated at a global scale to yield segmented structures. This method performs well under low signal-to-noise ratio typically found in tomograms of vitrified samples under cryo-tomography conditions and can bridge gaps present on membranes. The performance of the method is demonstrated by applications to tomograms of different biological samples and by quantitative comparison with standard template matching procedure. (C) 2014 Elsevier Inc. All rights reserved.

Details

show
hide
Language(s): eng - English
 Dates: 2014-04
 Publication Status: Published in print
 Pages: 13
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: ISI: 000334570200006
DOI: 10.1016/j.jsb.2014.02.015
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: JOURNAL OF STRUCTURAL BIOLOGY
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: 525 B ST, STE 1900, SAN DIEGO, CA 92101-4495 USA : ACADEMIC PRESS INC ELSEVIER SCIENCE
Pages: - Volume / Issue: 186 (1) Sequence Number: - Start / End Page: 49 - 61 Identifier: ISSN: 1047-8477