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