IS = { zkontrolovano 16 Jan 2013 },
  UPDATE  = { 2013-01-15 },
  author =       {Varray, Fran{\, c}ois and Kybic, Jan and 
                  Basset, Olivier and Cachard, Christian},
  title =        {Neuromuscular fiber segmentation using particle
                  filtering and discrete optimization},
  booktitle =    {MICCAI: Histopathology Image Analysis workshop},
  year =         {2012},
  isbn =         {},
  pages =        {48--59},
  book_pages =   {180},
  day =          {5},
  month =        {October},
  authorship =   {50-48-1-1},
  project =      {GACR P202/11/0111},
  venue =        {Nice, France},
  url = {{ftp://cmp.felk.cvut.cz/pub/cmp/articles/kybic/Varray-MICCAIHIMA2012.pdf}},
  annote = {We present an algorithm to segment a set of parallel,
    intertwined and bifurcating fibers from 3D images, targeted for
    identification of neuronal fibers in very large sets of 3D
    confocal microscopy images.  The method consists of preprocessing,
    local calculation of fiber probabilities, seed detection, local
    tracking by particle filtering, global supervised seed clustering,
    and final voxel segmentation.  The preprocessing uses a novel
    random local probability filtering segmentation. The global
    segmentation is solved by discrete optimization.  The combination
    of global and local approaches makes the segmentation robust, yet
    the individual data blocks can be processed sequentially, limiting
    memory consumption. The method is automatic but efficient manual
    interaction is possible if needed. Initial promising results on a
    neuromuscular projection fiber dataset as well as on simulated
    data are presented.},
  note =      {electronic (USB)},
  keywords = {neuronal fibers, tracking, microscopy, particles, probability filtering},