@Inproceedings{Borovec-Poster2013,
  IS = { zkontrolovano 12 Jan 2014 },
  UPDATE   = { 2014-01-06 },
  Title = {Fully automatic segmentation of stained histological cuts},
  author = {Borovec, Ji{\v r}{\'\i}},
  booktitle = {17th International Student Conference on Electrical Engineering},
pages       = { 1--7 },
  address = {Technick\'a 2, Prague, Czech Republic},
editor      = { Libor Husn{\'\i}k },
isbn        = { 978-80-01-05242-6 },
  day = {16},
  Month = {May},
  Year = {2013},
  Organization = {},
Publisher   = { Czech Technical University in Prague },
  Venue = {Praha, Czech Republic},
annote   = { The paper describes an automatic unsupervised
    segmentation of stained histological sections, which would
    be suitable for further registration of series of stained consecutive
    histological cuts. We combine some already existing
    methods - Gaussian Mixture model above colour histogram,
    superpixels to increase the robustness and speed and
    the Graph Cut method to obtain compact segmentation. We
    show the experimental results and segmentation precision on
    both synthetic and real histological images. For synthetic
    images we reach mean classification error for 4-class segmentation
    of about 3%. The unsupervised segmentation on
    real images shows us always reasonable object, which is important
    for future segmentation-based registration. },
  Keywords = {Superpixel, segmentation, GMM, Graph Cut, superpixels, histological sections, stains.},
  Project = {SGS12/190/OHK3/3T/13, GACR P202/11/0111, DPI2009-14115-C03-03, DPI2012-38090-C03-02},
  Psurl = {[Borovec-Poster2013.pdf]},
  Url = {ftp://cmp.felk.cvut.cz/pub/cmp/articles/borovec/Borovec-Poster2013.pdf},
book_pages  = { ? },
}