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XMSF: Structure-preserving noise reduction and pre-segmentation in microscope tomography.

Authors :
Bilbao-Castro, J. R.
Sorzano, C. O. S.
García, I.
Fernández, J. J.
Source :
Bioinformatics; Nov2010, Vol. 26 Issue 21, p2786-2787, 2p, 1 Black and White Photograph, 1 Diagram, 2 Charts
Publication Year :
2010

Abstract

Summary: Interpretation of electron tomograms is difficult due to the high noise levels. Thus, denoising techniques are needed to improve the signal-to-noise ratio. XMSF (Microscopy Mean Shift Filtering) is a fast, user-friendly application that succeeds in filtering noise while preserving the structures of interest. It is based on the extension to 3D of a method widely applied in other image processing fields under very different scenarios. XMSF has been tested for a variety of tomograms, showing a great potential to become a state-of-the-art filtering program in electron tomography. Applied iteratively, the algorithm yields pre-segmented volumes facilitating posterior segmentation tasks. Moreover, execution times remain low thanks to parallel computing techniques to exploit current multicore computers.Availability: http://sites.google.com/site/xmsfilter/Contact: jrbcast@ace.ual.es [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
13674803
Volume :
26
Issue :
21
Database :
Complementary Index
Journal :
Bioinformatics
Publication Type :
Academic Journal
Accession number :
54655355
Full Text :
https://doi.org/10.1093/bioinformatics/btq496