• DocumentCode
    2155776
  • Title

    Automatic Medical Image Annotation and Retrieval Using SECC

  • Author

    Yao, Jian ; Antani, Sameer ; Long, Rodney ; Thoma, George ; Zhang, Zhongfei

  • Author_Institution
    Dept. of Comput. Sci., State Univ. of New York, Binghamton, NY
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    820
  • Lastpage
    825
  • Abstract
    The demand for automatically annotating and retrieving medical images is growing faster than ever. In this paper, we present a novel medical image annotation method based on the proposed semantic error-correcting output codes (SECC). With this annotation method, we present a new semantic image retrieval method, which exploits the high level semantic similarity. For example, a user may query the system using an image of arm while he/she expects images of hand. This cannot be realized by traditional retrieval methods. The experimental results on the IMAGECLEF 2005 annotation data set clearly show the strength and the promise of the presented methods
  • Keywords
    error correction codes; image retrieval; medical image processing; automatic medical image annotation; medical image retrieval; semantic error-correcting output codes; semantic image retrieval method; Biomedical imaging; Computer science; Elbow; Foot; Image retrieval; Libraries; Medical diagnosis; Medical diagnostic imaging; Medical treatment; Surgery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Based Medical Systems, 2006. CBMS 2006. 19th IEEE International Symposium on
  • Conference_Location
    Salt Lake City, UT
  • ISSN
    1063-7125
  • Print_ISBN
    0-7695-2517-1
  • Type

    conf

  • DOI
    10.1109/CBMS.2006.57
  • Filename
    1647672