Skip to main content

Improving Early Precision in the ImageCLEF Medical Retrieval Task

  • Chapter
ImageCLEF

Part of the book series: The Information Retrieval Series ((INRE,volume 32))

Abstract

Oregon Health and Science University has participated in the ImageCLEFmed medical image retrieval task since 2005. Over the years of our participation, our focus has been on exploring the needs of medical end users, and developing retrieval strategies that address those needs. Given that many users of search systems never look beyond the first few results, we have attempted to emphasize early precision in the performance of our system. This chapter describes several of the approaches we have used to achieve this goal, along with the results we have seen in doing so.

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
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

  • Furnas GW, Deerwester S, Dumais ST, Landauer TK, Harshman RA, Streeter LA, Lochbaum KE (1988) Information retrieval using a singular value decomposition model of latent semantic structure. In: Proceedings of the 11th annual international ACM SIGIR conference on Research and development in information retrieval. ACM press, pp 465–480

    Google Scholar 

  • Güld MO, Kohnen M, Keysers D, Schubert H, Wein BB, Bredno J, Lehmann TM (2002) Quality of DICOM header information for image categorization. In: Siegel EL, Huang HK (ed) Society of Photo–Optical Instrumentation Engineers (SPIE) Conference Series, vol 4685, pp 280–287

    Google Scholar 

  • Hearst M (2009) Search user interfaces. Cambridge University Press, Cambridge

    Google Scholar 

  • Hersh W, Kalpathy-Cramer J, Jensen J (2006) Medical Image Retrieval and Automated Annotation: OHSU at ImageCLEF 2006. In: Peters C, Clough P, Gey FC, Karlgren J, Magnini B, Oard DW, de Rijke M, Stempfhuber M (eds) Proceesings of the Corss–Language Evaluation Forum. Lecture Notes in Computer Science (LNCS), vol 4730. Springer, pp 660–669

    Google Scholar 

  • Kalpathy-Cramer J, Hersh W (2007) Automatic image modality based classification and annotation to improve medical image retrieval. In: Studies in health technology and informatics, vol 129. IOS, pp 1334–1338

    Google Scholar 

  • Kalpathy-Cramer J, Hersh W (2008) Medical Image Retrieval and Automatic Annotation: OHSU at ImageCLEF 2007. In: Peters C, Valentin J, Mandl T, Müller H, Oard D, Petras A, Petras V, Santos D (eds) Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross–Language Evaluation Forum. Lecture Notes in Computer Science (LNCS), vol 5152. Springer, pp 623–630

    Google Scholar 

  • Kalpathy-Cramer J, Bedrick S, Lam CA, Eldredge C, Kahn Jr. CE (2009) Automated image–based classification of imaging modality. In: Proceedings of the 95th Scientific Assembly and Annual Meeting of the RSNA

    Google Scholar 

  • Müller H, Michoux N, Bandon D, Geissbuhler A (2004) A review of content–based image retrieval systems in medical applications—clinical benefits and future directions. International Journal of Medical Informatics 73(1):1–23

    Article  Google Scholar 

  • Müller H, Deselaers T, Deserno T, Clough P, Kim E, Hersh W (2007) Overview of the ImageCLEFmed 2006 medical retrieval and medical annotation tasks. In: Peters C, Clough P, Gey F, Karlgren J, Magnini B, Oard D, de Rijke M, Stempfhuber M (eds) Evaluation of Multilingual and Multi–modal Information Retrieval: Seventh Workshop of the Cross–Language Evaluation Forum, CLEF 2006. Lecture Notes in Computer Science (LNCS), vol 4730. Springer, pp 595–608

    Google Scholar 

  • Radhouani S (2008) Un modèle de recherche d’information orienté précision fondé sur les dimensions de domaine. PhD thesis, University of Geneva, Switzerland, and University of Grenoble, France

    Google Scholar 

  • Radhouni S, Kalpathy-Cramer J, Bedrick S, Bakke B, Hersh W (2009) Multimodal medical image retrieval improving precision at ImageCLEF 2009. In: Working Notes of CLEF 2009

    Google Scholar 

  • Smeulders A, Worring M, Santini S, Gupta A, Jain R (2000) Content–based image retrieval at the end of the early years. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(12):1349–1380

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Steven Bedrick .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Bedrick, S., Radhouani, S., Kalpathy–Cramer, J. (2010). Improving Early Precision in the ImageCLEF Medical Retrieval Task. In: Müller, H., Clough, P., Deselaers, T., Caputo, B. (eds) ImageCLEF. The Information Retrieval Series, vol 32. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15181-1_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-15181-1_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15180-4

  • Online ISBN: 978-3-642-15181-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics