2010Bilbao MeanShift
Citation
J.R. Bilbao-Castro, C.O.S. Sorzano, J.J. Fernández, I. García. XMSF: Structure-preserving noise reduction and pre-segmentation in microscope tomography. Bioinformatics, 26: 2786-2787 (2010)
Abstract
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/
Keywords
Denoising, tomograms, tomographs
Links
http://www.ncbi.nlm.nih.gov/pubmed/20802209
Related software
http://sites.google.com/site/xmsfilter