• DocumentCode
    635477
  • Title

    Maximizing structural similarity in multimodal biomedical microscopic images for effective registration

  • Author

    Guohua, L.V. ; Wei Shyh Teng ; Guojun Lu ; Lackmann, Martin

  • Author_Institution
    Gippsland Sch. of Inf. Technol., Monash Univ., Churchill, VIC, Australia
  • fYear
    2013
  • fDate
    15-19 July 2013
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Multimodal image registration (MMIR) is the alignment of contents in images captured from different sensors or instruments. MMIR is important in medical applications as it enables the visualization of the complementary contents in biomedical microscopic images. The registration for such images can be challenging as the structures of their contents are usually only partially similar. Thus in this paper, we propose a new method to maximize the structural similarity of the contents in such images by utilizing intensity relationships among Red-Green-Blue color channels. Our experimental results will demonstrate that our proposed method substantially improves the accuracy of registering such images as compared to the state-of-the-art methods.
  • Keywords
    image colour analysis; image matching; image registration; image sensors; medical image processing; microscopy; MMIR; complementary content visualization; content similarity; image capturing; image sensors; multimodal biomedical microscopic images; multimodal image registration; red-green-blue color channels; structural similarity maximization; Accuracy; Biomedical imaging; Color; Image color analysis; Image registration; Image segmentation; Microscopy; SIFT; Structural similarity; intensity relationship; multimodal image registration; staining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo (ICME), 2013 IEEE International Conference on
  • Conference_Location
    San Jose, CA
  • ISSN
    1945-7871
  • Type

    conf

  • DOI
    10.1109/ICME.2013.6607629
  • Filename
    6607629