Vessel boundary detection for its 3D reconstruction by using a deformable model (GVF Snake)

H. C. Kim, H. R. Kim, C. B. Ahn, G. S. Jeong, M. G. Kim, K. Sun

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    7 Citations (Scopus)

    Abstract

    Vessel boundary detection and 3D modeling is a difficult but necessary task in analyzing the mechanics of inflammation and the structure of the microvasculature. We present in this paper a method of analyzing this structure by the means of the deformable model (using GVF Snake) for vessel boundary detection and three-dimensional reconstruction. For this purpose, we used a virtual vessel model and produced synthetic images. From these images, we obtained contours of vessels by the GVF Snake and then reconstructed a three-dimensional structure by using the coordinates of the Snakes.

    Original languageEnglish
    Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages3440-3443
    Number of pages4
    ISBN (Print)0780387406, 9780780387409
    DOIs
    Publication statusPublished - 2005
    Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
    Duration: 2005 Sept 12005 Sept 4

    Publication series

    NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
    Volume7 VOLS
    ISSN (Print)0589-1019

    Other

    Other2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
    Country/TerritoryChina
    CityShanghai
    Period05/9/105/9/4

    Keywords

    • 3D reconstruction
    • Deformable model
    • Gradient vector flow
    • Snakes
    • Vessel boundary detection

    ASJC Scopus subject areas

    • Signal Processing
    • Biomedical Engineering
    • Computer Vision and Pattern Recognition
    • Health Informatics

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