• DocumentCode
    1821460
  • Title

    Automatic registration of large set of microscopic images using high-level features

  • Author

    Prescott, Jeffrey ; Clary, Matthew ; Wiet, Gregory ; Pan, Tony ; Huang, Kun

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Ohio State Univ., Columbus, OH
  • fYear
    2006
  • fDate
    6-9 April 2006
  • Firstpage
    1284
  • Lastpage
    1287
  • Abstract
    In this paper, we present a novel method for automatic registration of large set of microscopic images by automatically match high-level region features via finding cyclic structures in a matching graph. The use of high-level features (e.g., regions, landmarks, objects) significantly reduced the computation and provides accurate initialization, which further allows fast convergence of the maximum mutual information algorithm. The scheme is a universal one as it works for other types of high-level features and the matching process is very computationally efficient. We have applied our method in 3-D reconstruction of a unique human cochlear sample and are also applying it to two other set of large microscopic images
  • Keywords
    ear; image matching; image reconstruction; image registration; medical image processing; 3-D reconstruction; automatic microscopic image registration; cyclic structures; high-level features; human cochlear sample; matching graph; maximum mutual information algorithm; Biomedical informatics; Computer vision; Convergence; Ear; Humans; Microscopy; Mutual information; NP-complete problem; Three dimensional displays; Visualization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging: Nano to Macro, 2006. 3rd IEEE International Symposium on
  • Conference_Location
    Arlington, VA
  • Print_ISBN
    0-7803-9576-X
  • Type

    conf

  • DOI
    10.1109/ISBI.2006.1625160
  • Filename
    1625160