• DocumentCode
    3040365
  • Title

    5.8: Presentation session: Neuroscience informatics: “Fully automated segmentation and characterization of the dendritic trees of retinal horizontal neurons”

  • Author

    Kerekes, Ryan

  • Author_Institution
    Measurement Sciences and Systems Engineering Division, Oak Ridge National Laboratory
  • fYear
    2010
  • fDate
    25-26 May 2010
  • Firstpage
    1
  • Lastpage
    1
  • Abstract
    We introduce a new fully automated method for segmenting and characterizing the dendritic tree of neurons in confocal image stacks. Our method is aimed at wide-field-of-view, low-resolution imagery of retinal neurons in which dendrites can be intertwined and difficult to follow. The approach is based on 3-D skeletonization and includes a method for automatically determining an appropriate global threshold as well as a soma detection algorithm. We provide the details of the algorithm and a qualitative performance comparison against a commercially available neurite tracing software package, showing that a segmentation produced by our method more closely matches the ground-truth segmentation.
  • Keywords
    Detection algorithms; Image segmentation; Informatics; Laboratories; Neurons; Neuroscience; Retina; Software algorithms; Systems engineering and theory; Time measurement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Sciences and Engineering Conference (BSEC), 2010
  • Conference_Location
    Oak Ridge, TN, USA
  • Print_ISBN
    978-1-4244-6713-6
  • Electronic_ISBN
    978-1-4244-6714-3
  • Type

    conf

  • DOI
    10.1109/BSEC.2010.5510844
  • Filename
    5510844