• DocumentCode
    3152241
  • Title

    Skeleton extraction of cerebral vascular image based on topology node

  • Author

    Qi, Aipeng ; Xu, Jing

  • Author_Institution
    Dept. of Comput. Eng., Henan Ind. & Trade Vocational Collage, Zhengzhou, China
  • Volume
    2
  • fYear
    2010
  • fDate
    16-18 Oct. 2010
  • Firstpage
    569
  • Lastpage
    573
  • Abstract
    Skeleton extraction has important application value on object recognition, shape retrieval and feature extraction. Traditional skeleton extraction methods more or less have some flaws. Due to the complexity and diversity of cerebral blood vessels images, the traditional skeleton extraction algorithm can not often get continuous skeletons. This paper presents a new framework to calculate the continuous brain blood vessel skeleton curves of binary images and gray-scale images. Algorithm first determines the shape topology nodes of objects, then extract skeletons using the topology nodes as sources point. Experiment and analysis can verify the validity and robustness of this method and it is not sensitive to the boundary noise. This electronic document is a “live” template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.
  • Keywords
    blood vessels; bone; brain; feature extraction; medical image processing; object recognition; binary images; cerebral vascular image; continuous brain blood vessel skeleton curves; feature extraction; gray-scale images; object recognition; shape retrieval; shape topology node; skeleton extraction; Algorithm design and analysis; Feature extraction; Gray-scale; Shape; Skeleton; Surface waves; Topology; Level Set Model; binary image and gray-scale image; skeleton extraction; topology node;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4244-6495-1
  • Type

    conf

  • DOI
    10.1109/BMEI.2010.5640001
  • Filename
    5640001