• DocumentCode
    651868
  • Title

    Tissue Surface Model Mapping onto Arbitrary Target Surface Based on Self-Organizing Deformable Model

  • Author

    Miyauchi, Shoko ; Morooka, Ken´ich ; Miyagi, Yasushi ; Fukuda, Toshio ; Tsuji, Takao ; Kurazume, Ryo

  • Author_Institution
    Grad. Sch. of Inf. Sci. & Electr. Eng., Kyushu Univ., Fukuoka, Japan
  • fYear
    2013
  • fDate
    9-11 Sept. 2013
  • Firstpage
    79
  • Lastpage
    82
  • Abstract
    This paper proposes a new method for mapping a tissue surface model onto an arbitrary target surface while preserving the geometrical features of the tissue surface. In our method, firstly, the tissue model is roughly deformed by using Self-organizing Deformable Model. Since the deformed model may contain folded patches, the folded patches are removed. Moreover, by Free-Form Deformation (FFD), and the area- and angle-preserving mapping, the model is mapped onto the target surface while preserving geometrical properties of the original model. From several experimental results, we can conclude that the proposed method can map tissue models onto arbitrary target surface without foldovers.
  • Keywords
    biological tissues; deformation; medical image processing; statistical analysis; FFD; angle-preserving mapping; arbitrary target surface; area-preserving mapping; folded patches; free-form deformation; geometrical feature preserving; medical images; self-organizing deformable model; tissue surface model mapping; Biomedical imaging; Brain modeling; Computational modeling; Deformable models; Rough surfaces; Shape; Surface roughness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Emerging Security Technologies (EST), 2013 Fourth International Conference on
  • Conference_Location
    Cambridge
  • Type

    conf

  • DOI
    10.1109/EST.2013.34
  • Filename
    6680192