title: XMSF: Structure-preserving noise reduction and pre-segmentation in microscope tomography.
abstract: CONCLUSIONS
  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.
  
  
  BACKGROUND
  http://sites.google.com/site/xmsfilter/
authors.affiliation: Department of Computer Architecture and Electronics, University de Almería, Almería, Spain. jrbcast@ace.ual.es
authors.forename: J R
authors.initials: JR
authors.lastname: Bilbao-Castro
authors.forename: C O S
authors.initials: CO
authors.lastname: Sorzano
authors.forename: I
authors.initials: I
authors.lastname: García
authors.forename: J J
authors.initials: JJ
authors.lastname: Fernández
mesh_terms: D000465:Algorithms; D055032:Electron Microscope Tomography / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D021621:Imaging, Three-Dimensional / Q000379:methods*; D012680:Sensitivity and Specificity; D012984:Software