Skip to main content

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4730))

Included in the following conference series:

Abstract

This paper presents the results of the University at Buffalo in the 2006 ImageCLEFmed task. Our approach for this task combines Content Based Image Retrieval (CBIR) and text retrieval to improve retrieval of medical images. Our results are comparable to other approaches presented in the task. Our results show that text retrieval performs well across the three different types of topics (visual, visual-semantic and semantic) and that the combination of CBIR and text retrieval yields moderate improvements.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Rocchio, J.J.: Relevance feedback in information retrieval. In: Salton, G. (ed.) The SMART Retrieval System: Experiments in Automatic Document Processing, Englewood Cliff, NJ (1971)

    Google Scholar 

  2. Ruiz, M.: Combining image features, case descriptions and umls concepts to improve retrieval of medical images. In: Proceedings of the American Medical Informatics Association 2006 Annual Symposium, Washington, DC, pp. 674–678 (2006)

    Google Scholar 

  3. Ruiz, M., Southwick, S.: Ub at clef 2005: Bilingual portuguese and medical image retrieval tasks. In: Peters, C., Gey, F.C., Gonzalo, J., Müller, H., Jones, G.J.F., Kluck, M., Magnini, B., de Rijke, M., Giampiccolo, D. (eds.) CLEF 2005. LNCS, vol. 4022, Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  4. Ruiz, M., Srikanth, M.: Ub at clef 2004: Cross language medical image retrieval. In: Peters, C., Clough, P.D., Gonzalo, J., Jones, G.J.F., Kluck, M., Magnini, B. (eds.) CLEF 2004. LNCS, vol. 3491, pp. 773–780. Springer, Heidelberg (2005)

    Google Scholar 

  5. Salton, G. (ed.): The SMART Retrieval System: Experiments in Automatic Document Processing. Prentice-Hall, Englewood Cliffs, NJ (1983)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Carol Peters Paul Clough Fredric C. Gey Jussi Karlgren Bernardo Magnini Douglas W. Oard Maarten de Rijke Maximilian Stempfhuber

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ruiz, M.E. (2007). UB at ImageCLEFmed 2006. In: Peters, C., et al. Evaluation of Multilingual and Multi-modal Information Retrieval. CLEF 2006. Lecture Notes in Computer Science, vol 4730. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74999-8_87

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74999-8_87

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74998-1

  • Online ISBN: 978-3-540-74999-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics