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Oxford University Press (OUP), Bioinformatics, 21(26), p. 2786-2787

DOI: 10.1093/bioinformatics/btq496

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

Journal article published in 2010 by J. R. Bilbao Castro, C. O. S. Sorzano ORCID, I. García, J. J. Fernández
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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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/