Skip to main content
SpringerLink
Log in

Fusion Techniques in Biomedical Information Retrieval

  • Chapter
  • First Online:
Book cover Fusion in Computer Vision

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

For difficult cases clinicians usually use their experience and also the information found in textbooks to determine a diagnosis. Computer tools can help them supply the relevant information now that much medical knowledge is available in digital form. A biomedical search system such as developed in the Khresmoi project (that this chapter partially reuses) has the goal to fulfil information needs of physicians. This chapter concentrates on information needs for medical cases that contain a large variety of data, from free text, structured data to images. Fusion techniques will be compared to combine the various information sources to supply cases similar to an example case given. This can supply physicians with answers to problems similar to the one they are analyzing and can help in diagnosis and treatment planning.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 54.99
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

Notes

  1. 1.

    http://medical.novasearch.org/

  2. 2.

    http://lucene.apache.org/

  3. 3.

    http://terrier.org/

  4. 4.

    http://orpheus.ee.duth.gr/anaktisi/

  5. 5.

    http://thomas.deselaers.de/fire/

  6. 6.

    http://www.lire-project.net/

  7. 7.

    http://goldminer.arrs.org/

  8. 8.

    http://www.yottalook.com/

  9. 9.

    http://imageclef.org/

  10. 10.

    http://imageclef.org/

  11. 11.

    http://www.clef-initiative.eu/

  12. 12.

    http://www.khresmoi.eu/

References

  1. Aamodt A, Plaza E (1994) Case-based reasoning: foundational issues, methodological variations, and systems approaches. AIC 7(1):39–59

    Google Scholar 

  2. Apostolova E, You D, Xue Z, Antani S, Demner-Fushman D, Thoma GR (2013) Image retrieval from scientific publications: text and image content processing to separate multi-panel figures. J Am Soc Inf Sci Technol 64(5):893–908

    Google Scholar 

  3. Aswani N, Beckers T, Birngruber E, Boyer C, Burner A, Bystron J, Choukri K, Cruchet S, Cunningham H, Dedek J, Dolamic L, Donner R, Dungs S, Eggel I, Foncubierta-Rodríguez A, Fuhr N, Funk A, García Seco de Herrera A, Gaudinat A, Georgiev G, Gobeill J, Goeuriot L, Gómez P, Greenwood M, Gschwandtner M, Hanbury A, Hajic J, Hlavácová J, Holzer M, Jones G, Jordan B, Jordan M, Kaderk K, Kainberger F, Kelly L, Mriewel S, Kritz M, Langs G, Lawson N, Markonis D, Martinez I, Momtchev V, Masselot A, Mazo H, Müller H, Pecina P, Pentchev K, Peychev D, Pletneva N, Pottecherc D, Roberts A, Ruch P, Samwald M, Schneller P, Stefanov V, Tinte MA, Uresová Z, Vargas A, Vishnyakova D (2012) Khresmoi: multimodal multilingual medical information search. In: Proceedings of the 24th international conference of the European federation for medical informatics

    Google Scholar 

  4. Begum S, Ahmed MU, Funk P, Xiong N, Folke M (2011) Case-based reasoning systems in the health sciences: a survey of recent trends and developments. IEEE Trans Syst Man Cybern 41(4):421–434

    Article  Google Scholar 

  5. Burghouts GJ, Geusebroek JM (2009) Performance evaluation of local colour invariants. Comput Vis Image Underst 113(1):48–62

    Article  Google Scholar 

  6. Caputo B, Müller H, Thomee B, Villegas M, Paredes R, Zellhofer D, Goeau H, Joly A, Bonnet P, Martinez Gomez J, Garcia Varea I, Cazorla C (2013) ImageCLEF 2013: the vision, the data and the open challenges. In: Working notes of CLEF 2013 (Cross Language Evaluation Forum)

    Google Scholar 

  7. Chatzichristofis SA, Boutalis YS (2008) Cedd: color and edge directivity descriptor: a compact descriptor for image indexing and retrieval. Lect Notes Comput Sci 5008:312–322

    Article  Google Scholar 

  8. Chatzichristofis, SA, Boutalis YS (2008) FCTH: fuzzy color and texture histogram: a low level feature for accurate image retrieval. In: Proceedings of the 9th international workshop on image analysis for multimedia interactive service, pp 191–196

    Google Scholar 

  9. Cheng B, Sameer A, Stanley RJ, Thoma GR (2011) Automatic segmentation of subfigure image panels for multimodal biomedical document retrieval. In: Agam G, Viard-Gaudin C (eds.) Document recognition and retrieval. SPIE Proceedings, SPIE, vol 7874, pp 1–10

    Google Scholar 

  10. Cheng B, Stanley RJ, De S, Antani S, Thoma GR (2011) Automatic detection of arrow annotation overlays in biomedical images. Int J Healthc Inf Syst Inform 6(4):23–41

    Article  Google Scholar 

  11. Chhatkuli A, Markonis D, Foncubierta-Rodríguez A, Meriaudeau F, Müller H (2013) Separating compound figures in journal articles to allow for subfigure classification. In: SPIE medical imaging

    Google Scholar 

  12. Chiu P, Chen F, Denoue L (2010) Picture detection in document page images. In: Proceedings of the 10th ACM symposium on document engineering, pp 211–214, ACM

    Google Scholar 

  13. Demner-Fushman D, Antani S, Simpson MS, Thoma GR (2012) Design and development of a multimodal biomedical information retrieval system. J Comput Sci Eng 6(2):168–177

    Article  Google Scholar 

  14. Depeursinge A, Müller H (2010) Fusion techniques for combining textual and visual information retrieval. In: Müller H, Clough P, Deselaers T, Caputo B (eds) ImageCLEF, The Springer international series on information retrieval, vol 32. Springer, Berlin Heidelberg, pp 95–114

    Google Scholar 

  15. Glasgow J, Jurisica I (1998) Integration of case-based and image-based reasoning. In: AAAI workshop on case-based reasoning integrations. AAAI Press, Menlo Park, California, pp 67–74

    Google Scholar 

  16. Gu M, Aamodt A, Tong X (2005) Component retrieval using conversational case-based reasoning. In: Intelligent information processing II. Springer-Verlag, London, UK, pp 259–271

    Google Scholar 

  17. García Seco de Herrera A, Kalpathy-Cramer J, Demner Fushman D, Antani S, Müller H (2013) Overview of the ImageCLEF 2013 medical tasks. In: Working notes of CLEF 2013 (Cross Language Evaluation Forum)

    Google Scholar 

  18. García Seco de Herrera A, Markonis D, Eggel I, Müller H (2012) The medGIFT group in ImageCLEFmed 2012. In: Working notes of CLEF 2012

    Google Scholar 

  19. García Seco de Herrera A, Markonis D, Müller H (2013) Bag of colors for biomedical document image classification. In: Greenspan H, Müller H (eds) Medical content-based retrieval for clinical decision support. In: MCBR-CDS 2012. Lecture Notes in Computer Sciences (LNCS), pp 110–121

    Google Scholar 

  20. García Seco de Herrera A, Markonis D, Schaer R, Eggel I, Müller H (2013) The medGIFT group in ImageCLEFmed 2013. In: Working notes of CLEF 2013 (Cross Language Evaluation Forum)

    Google Scholar 

  21. García Seco de Herrera A, Schaer R, Müller H (submitted) Comparing fusion techniques for the ImageCLEF 2013 medical case retrieval task. Comput Med Imaging Graph

    Google Scholar 

  22. Hwang HK, Lee H, Choi D (2012) Medical image retrieval: past and present. Healthc Inf Res 18(1):3–9

    Article  Google Scholar 

  23. Ide NC, Loane RF, Demner-Fushman D (2007) Essie: a concept-based search engine for structured biomedical text. J Am Med Inform Assoc 14(3):253–263

    Article  Google Scholar 

  24. Kalpathy-Cramer J, Hersh W (2010) Multimodal medical image retrieval: image categorization to improve search precision. In: Proceedings of the international conference on multimedia information retrieval, MIR ’10ACM, New York, NY, USA, pp 165–174

    Google Scholar 

  25. Kwiatkowska M, Atkins S (2004) Case representation and retrieval in the diagnosis and treatment of obstructive sleep apnea: a semiofuzzy approach. In: Proceedings European case based reasoning conference, ECCBR’04

    Google Scholar 

  26. Lazebnik S, Schmid C, Ponce J (2006) Beyond bags of features: spatial pyramid matching for recognizing natural scene categories. In: Proceedings of the 2006 IEEE conference on computer vision and pattern recognition, CVPRIEEE Computer Society, Washington, DC, USA, pp 2169–2178

    Google Scholar 

  27. Li Y, Shi N, Frank DH (2011) Fusion analysis of information retrieval models on biomedical collections. In: Proceedings of the 14th international conference on information fusion. IEEE Computer Society

    Google Scholar 

  28. Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91–110

    Article  Google Scholar 

  29. Markonis D, García Seco de Herrera A, Eggel I, Müller H (2011) The medGIFT group in ImageCLEFmed 2011. In: Working notes of CLEF 2011

    Google Scholar 

  30. Markonis D, Holzer M, Dung S, Vargas A, Langs G, Kriewel S, Müller H (2012) A survey on visual information search behavior and requirements of radiologists. Methods Inf Med 51(6):539–548

    Article  Google Scholar 

  31. McCandless M, Hatcher E, Gospodnetic O (2010) Lucene in action, second edition: Covers Apache Lucene 3.0. Manning Publications, Greenwich, CT, USA

    Google Scholar 

  32. Montani S, Bellazzi R (2002) Supporting decisions in medical applications: the knowledge management perspective. Int J Med Inform 68:79–90

    Article  Google Scholar 

  33. Mourão A, Martins F (2013) NovaMedsearch: a multimodal search engine for medical case-based retrieval. In: Proceedings of the 10th conference on open research areas in information retrieval, OAIR’13, pp 223–224

    Google Scholar 

  34. Müller H, Boyer C, Gaudinat A, Hersh W, Geissbuhler A (2007) Analyzing web log files of the health on the Net HONmedia search engine to define typical image search tasks for image retrieval evaluation. MedInfo 2007, vol 12. Studies in health technology and informatics. IOS press, Brisbane, Australia, pp 1319–1323

    Google Scholar 

  35. Müller H, Despont-Gros C, Hersh W, Jensen J, Lovis C, Geissbuhler A (2006) Health care professionals’ image use and search behaviour. Proceedings of the medical informatics Europe conference (MIE 2006). Studies in health technology and informatics. IOS Press, Maastricht, The Netherlands, pp 24–32

    Google Scholar 

  36. Müller H, García Seco de Herrera A, Kalpathy-Cramer J, Demner Fushman D, Antani S, Eggel I (2012) Overview of the ImageCLEF 2012 medical image retrieval and classification tasks. In: Working notes of CLEF 2012 (Cross Language Evaluation Forum)

    Google Scholar 

  37. Müller H, Zhou X, Depeursinge A, Pitkanen M, Iavindrasana J, Geissbuhler A (2007) Medical visual information retrieval: state of the art and challenges ahead. In: Proceedings of the 2007 IEEE international conference on multimedia and Expo, ICME’07, IEEE, pp 683–686

    Google Scholar 

  38. Philip A, Afolabi B, Oluwaranti A, Oluwatolani O (2011) Development of an image retrieval model for biomedical image databases. In: Jao C (ed) ISBN: 978-953-307-258-6, InTech, Available from: http://www.intechopen.com/books/efficient-decision-support-systems-practice-and-challenges-in-biomedical-related-domain/development-of-an-image-retrieval-model-for-biomedical-image-databases

  39. Quellec G, Lamard M, Bekri L, Cazuguel G, Roux C, Cochener B (2010) Medical case retrieval from a committee of decision trees. IEEE Trans Inf Technol Biomed 14(5):1227–1235

    Article  Google Scholar 

  40. Rahman MM, You D, Simpson MS, Antani S, Demner-Fushman D, Thoma GR (2012) An interactive image retrieval framework for biomedical articles based on visual region-of-interest (ROI) identification and classification. In: Proceedings of the IEEE second international conference on healthcare informatics, imaging and systems biology, HISB

    Google Scholar 

  41. Rahman MM, You D, Simpson MS, Antani SK, Demner-Fushman D, Thoma GR (2013) Multimodal biomedical image retrieval using hierarchical classification and modality fusion. Int J Multimedia Inf Retrieval 2(3):159–173

    Article  Google Scholar 

  42. van de Sande KEA, Gevers T, Smeulders AWM (2010) The university of amsterdam’s concept detection system at imageclef 2009. Lect Notes Comput Sci 6242:261–268

    Article  Google Scholar 

  43. Selvarajah S, Kodituwakku SR (2011) Analysis and comparison of texture features for content based image retrieval. Int J Latest Trends Comput 2:108–113

    Google Scholar 

  44. Seo M, Ko B, Chung H, Nam J (2006) ROI-based medical image retrieval using human-perception and MPEG-7 visual descriptors. Proceedings of the 5th international conference on image and video retrieval, CIVR’06. Springer-Verlag, Berlin, Heidelberg, pp 231–240

    Google Scholar 

  45. Shapiro LG, Atmosukarto I, Cho H, Lin HJ, Ruiz-Correa S, Yuen J (2008) Similarity-based retrieval for biomedical applications. In: Case-based reasoning on images and signals, Studies in computational intelligence, vol 73. Springer, pp 355–387

    Google Scholar 

  46. Simonyan K, Modat M, Ourselin S, Criminisi A, Zisserman A (2013) Immediate ROI search for 3-D medical images. In: Greenspan H, Müller H (eds) Medical content-based retrieval for clinical decision support. In: MCBR-CDS 2012. Lecture Notes in Computer Sciences (LNCS)

    Google Scholar 

  47. Simpson MS, Demner-Fushman D (2012) Biomedical text mining: a survey of recent progress. In: Aggarwal CC, Zhai C (eds) Mining text data. Springer, pp 465–517

    Google Scholar 

  48. Snoek CGM, Worring M, Smeulders AWM (2005) Early versus late fusion in semantic video analysis. In: MULTIMEDIA ’05: Proceedings of the 13th annual ACM international conference on multimedia, pp 399–402. ACM, New York, NY, USA

    Google Scholar 

  49. Tirilly P, Lu K, Mu X, Zhao T, Cao Y (2011) On modality classification and its use in text-based image retrieval in medical databases. In: 9th international workshop on content-based multimedia indexing

    Google Scholar 

  50. Tsikrika T, Müller H, Kahn Jr, CE (2012) Log analysis to understand medical professionals’ image searching behaviour. In: Proceedings of the 24th European medical informatics conference, MIE’2012

    Google Scholar 

  51. Wang JZ (2000) Region-based retrieval of biomedical images. In: Proceedings of the ACM multimedia conference, pp 511–512

    Google Scholar 

  52. Welter P, Deserno TM, Fischer B, Günther RW, Spreckelsen C (2011) Towards case-based medical learning in radiological decision making using content-based image retrieval. BMC Med Inform Decis Mak 11:68

    Article  Google Scholar 

  53. Zhang D, Lu G (2004) Review of shape representation and description techniques. Pattern Recogn 37(1):1–19

    Article  MATH  Google Scholar 

Download references

Acknowledgments

This work was partly supported by the EU 7th Framework Program in the context of the Khresmoi project (FP7-257528).

Author information

Authors and Affiliations

  1. University of Applied Sciences Western Switzerland (HES-SO), TechnoArk 3, 3960, Sierre, Switzerland

    Alba García Seco de Herrera & Henning Müller

Authors
  1. Alba García Seco de Herrera
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Henning Müller
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alba García Seco de Herrera .

Editor information

Editors and Affiliations

  1. University Politehnica of Bucharest, Romania

    Bogdan Ionescu

  2. University of Bordeaux, Talence, France

    Jenny Benois-Pineau

  3. Queen Mary University of London, London, United Kingdom

    Tomas Piatrik

  4. Lab. of Informatics of Grenoble, France

    Georges Quénot

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

García Seco de Herrera, A., Müller, H. (2014). Fusion Techniques in Biomedical Information Retrieval. In: Ionescu, B., Benois-Pineau, J., Piatrik, T., Quénot, G. (eds) Fusion in Computer Vision. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-319-05696-8_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-05696-8_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05695-1

  • Online ISBN: 978-3-319-05696-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation