A Software Framework for Combining Iconic and Semantic Content for Retrieval of Histological Images

  • Kent K. T. Cheung
  • Ringo W. K. Lam
  • Horace H. S. Ip
  • Lilian H. Y. Tang
  • Rudolf Hanka
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1929)


Content-based Image Retrieval (CBIR) is becoming an important component of a database system as it allows retrieval of images by objective measures such as color and texture. Nevertheless, retrieval of images intelligently by computer is still not common. In addition, different users might have different requirements so we need to address their needs by providing a more flexible retrieval mechanism. Finally, we might want to add CBIR functionality to existing system but none of the existing techniques is able to do this easily because they usually rely on one single environment. In this paper, we describe the design of a histological image retrieval system (I-Browse) that addresses the above three issues.


Image Retrieval Semantic Content Query Image Index Scheme Histological Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Kent K. T. Cheung
    • 1
  • Ringo W. K. Lam
    • 1
  • Horace H. S. Ip
    • 1
  • Lilian H. Y. Tang
    • 2
  • Rudolf Hanka
    • 2
  1. 1.City University of Hong KongKowloon TongHong Kong
  2. 2.Medical Informatics Unit, Medical SchoolUniversity of CambridgeUK

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