• DocumentCode
    2809160
  • Title

    A local maximum intensity projection tracing of vasculature in Knife-Edge Scanning Microscope volume data

  • Author

    Han, Donghyeop ; Keyser, John ; Choe, Yoonsuck

  • Author_Institution
    Dept. of Comput. Sci., Texas A&M Univ., College Station, TX, USA
  • fYear
    2009
  • fDate
    June 28 2009-July 1 2009
  • Firstpage
    1259
  • Lastpage
    1262
  • Abstract
    A local maximum intensity projection (MIP) approach to the extraction of a 3D vascular network, acquired by the Knife-Edge Scanning Microscope (KESM), is presented. We build a local volume for local MIP processing at each tracing step in order to reduce the dimension of input data from 3D to 2D, which leads to a 65.22% reduction of computation time compared to 3D tracing method. The proposed method makes use of existing 2D tracing methods, extending them into a 3D tracing method. Our experimental results show that our approach can rapidly and accurately extract the medial axis of vascular data acquired by the KESM.
  • Keywords
    biomedical optical imaging; blood vessels; brain; feature extraction; medical image processing; neurophysiology; optical microscopy; 2D tracing method; 3D neuronal vascular network extraction; 3D tracing method; KESM; MIP approach; brain vasculature; computation time reduction; input dimension reduction; knife-edge scanning microscope volume data; local MIP processing; local maximum intensity projection tracing; medial axis vascular data extraction; Computational complexity; Computer science; Data mining; Filters; Intelligent networks; Kernel; Medical conditions; Mice; Microscopy; Object detection; Dimension Reduction; Hessian Filter; Local MIP; Tracing; Vasculature;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
  • Conference_Location
    Boston, MA
  • ISSN
    1945-7928
  • Print_ISBN
    978-1-4244-3931-7
  • Electronic_ISBN
    1945-7928
  • Type

    conf

  • DOI
    10.1109/ISBI.2009.5193291
  • Filename
    5193291