Natural language processing versus content-based image analysis for medical document retrieval

Journal of the American Society for Information Science and Technology

Volumn 60, Issue 1, 2009, Pages 123-134

  Névéol, Aurélie ^a   Deserno, Thomas M ^a,b   Darmoni, Stefan J ^c   Güld, Mark Oliver ^b   Aronson, Alan R ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

^b RWTH AACHEN UNIVERSITY   (Germany)

^c ROUEN UNIVERSITY HOSPITAL   (France)

Author keywords

[No Author keywords available]

Indexed keywords

CONTENT-BASED; DOCUMENT ANALYSIS; DOCUMENT RETRIEVAL; HEALTH INFORMATION SYSTEMS; HEALTH RECORDS; IMAGE COMPONENTS; MULTI-MODAL; MULTIMODAL ANALYSIS; NATURAL LANGUAGE PROCESS (NLP); NATURAL LANGUAGE PROCESSING (NLP); TEXT ANALYSIS;

COMPUTATIONAL LINGUISTICS; IMAGE ANALYSIS; IMAGE PROCESSING; INDEXING (OF INFORMATION); LINGUISTICS; NATURAL LANGUAGE PROCESSING SYSTEMS; RECORDS MANAGEMENT; SECURITY OF DATA; WORD PROCESSING;

INDUSTRIAL RESEARCH;

EID: 58449125014     PISSN: 15322882     EISSN: 15322890     Source Type: Journal    
DOI: 10.1002/asi.20955     Document Type: Article

References (39)

1. Aachen University of Technology. (2008). Image retrieval in medical applications. Retrieved March 28, 2008, from http://www.irma-project.org/index- en.php
2. Aronson, A.R., Bodenreider, O., Demner-Fushman, D., Fung, K.W., Lee, V.K., Mork, J.G., et al. (2007). From indexing the biomedical literature to coding clinical text : Experience with MTI and machine learning approaches. In K. Cohen, D. Demner-Fushman, C. Friedman, L. Hirschman, & J. Pestian (Eds.), Proceedings of the ACL 2007 Workshop on Biological, Translational, and Clinical Language Processing (BioNLP) (pp. 105-112).
3. Boujemaa, N., Fauqueur, J., & Gouet, V. (2003, June). IAPR International Conference on Image and Signal Processing (ICISP'2003), Agadir, Morocco. What's beyond query by example? Retrieved August 29, 2008, from http://www-rocq.inria.fr/̃gouet/Recherche/Papiers/icisp03/pdf
4. Briet, S. (1951). Qu'est-ce que 1a documentation? [What is documentation?] Paris: Editions Documentaires et Industrielles. [English translation retrieved April 29, 2007, from http://martinetl.free.fr/suzanne- briet.htm and archived at http://www.webcitation.org/50UOoaTjW]
5. Byrne, K., & Klein, E. (2003). Image retrieval using natural language and content-based techniques. In A.P. de Vries (Ed.), Proceedings of the Fourth Dutch-Belgian Information Retrieval Workshop (DIR 2003) (pp. 57-62). Amsterdam: Institute for Logic, Language, and Computation.
6. Chang, C.H., Kayed, M. Girgis, M.R., & Shaalan K. (2006). A survey of Web information extraction systems. IEEE Transactions on Knowledge and Data Engineering, 18, 1411-1428.
7. Christiansen, A., Lee, DJ., & Chang, Y. (2007). Finding relevant PDF medical journal articles by the content of their figures. In S.C. Horii & K.P. Andriole (Eds.), Medical Imaging 2007: PACS and Imaging Informatics. Proceedings of the International Society for Optical Engineering (SPIE), 6516, OK1-OK12.
8. CHU de Rouen. (2008). Catalogue et Index des Sites Medicaux Francophones [Catalog and index of online health information in French]. Retrieved March 28, 2008, from http://www cismef.org
9. Deerwester, S., Dumais, S., Furnas, G., Landauer, T, &Harshman, R. (1990). Indexing by latent semantic analysis. Journal of American Society for Information Science, 6, 391-407.
10. Deselaers, T, Muller, H. Clough, P., Ney, H., & Lehmann, TM. (2007). The CLEF 2005 automatic medical image annotation task. International Journal of Computer Vision, 74, 51-58.
11. Deserno, T.M., Antani, S., & Long, L.R. (2007). Exploring access to scientific literature using content-based image retrieval. Proceedings of the International Society for Optical Engineering (SPIE), 6516, OL1-OL8.
12. Florea, F.I. (2006). Combining textual and visual information for automatic annotation of online medical images (Technical Report). Rouen, France: Laboratoire LITIS.
13. Haralick, R.M., Shanmugam, K., & Dinstein, I. (1973).Textural features for image classification. IEEE Transactions on Systems, Man, and Cybernetics, 3, 610-621.
14. Haux, R. (2006). Health information systems: Past, present, and future. International Journal of Medical Informatics, 75, 268-281.
15. Hersh, W.R., Muller, H., Jensen, J.R., Yang, J., Gorman, P.N., & Ruch, P. (2006). Advancing biomedical image retrieval: Development and analysis of a test collection. Journal of the American Medical Informatics Association, 13, 488-496.
16. Hripcsak, G., & Rothschild, A.S. (2005). Agreement, the f-measure, and reliability in information retrieval. Journal of the American Medical Informatics Association, 12, 296-298.
17. Kahn, C.E., & Thao, C. (2007). GoldMiner: A radiology image search engine. American Journal of Roentgenology, 188, 1475-1478.
18. Keysers, D., Dahmen, J., Ney, H., Wein, B.B., & Lehmann, T.M. (2003). A statistical framework for model-based image retrieval in medical applications. Journal of Electronic Imaging, 12, 59-68.
19. Lehmann, T.M. (2002). From plastic to gold: A unified classification scheme for reference standards in medical image processing. Proceedings of the International Society for Optical Engineering (SPIE), 4684, 1819-1827.
20. Lehmann, T.M., Güld, M.O., Thies, C, Fischer, B., Spitzer, K., Keysers, D., et al. (2004). Content-based image retrieval in medical applications. Methods of Information in Medicine, 43, 354-361.
21. Lehmann, T.M., Schubert, H., Keysers, D., Kohnen, M., & Wein, B.B. (2003). The IRMA code for unique classification of medical images. Proceedings of the International Society for Optical Engineering (SPIE), 5033, 109-117.
22. Lowe, H.J., Antipov, I. Hersh, W. & Smith, CA. (1998). Towards knowledge-based retrieval of medical images. The role of semantic indexing, image content representation, and knowledge-based retrieval. In Proceedings of the American Medical Informatics Association (AMIA) Symposium (pp. 882-886).
23. Mougin, F, & Bodenreider, O. (2005). Approaches to eliminating cycles in the UMLS Metathesaurus: Naive vs. formal. In Proceedings of the American Medical Informatics Association (AMIA) Fall Symposium (pp. 550-554).
24. Muller, H., Deselaers, T., Deserno, T.M., Clough, P., Kim, E., & Hersch, W. (2007). Overview of the ImageCLEFmed 2006 medical retrieval and annotation tasks. In C. Peters, P. Clough, F. Gey, J. Karlgren, B. Magnini, D.W. Oard, M. de Rijke, M. Stempfhuber (Eds.), Evaluation of Multilingual and Multi-modal Information Retrieval - 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006. Lecture Notes in Computer Science, vol. 4730 (pp. 595-608). New York: Springer Verlag.
25. Muller, H. Geissbuhler, A., & Ruch, P. (2005). ImageCLEF 2004: Combining image and multilingual search for medical image retrieval. In Lecture Notes in Computer Science, Vol. 3491: Cross Language Evaluation Forum (CLEF 2004) (pp. 718-727). Berlin: Springer Verlag.
26. Muller, 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, 1-23.
27. Névéol, A., Douyére, M., Rogozan, A., &Darmoni, S.J. (2007). Construction de ressources terminologiques en santé [Development of health terminology resources]. In S. Koeva, D. Maurel, & M. Silberztein (Eds.), Formaliser les langues avec 1' ordinateur [Formalizing languages with the computer], (pp. 171-187). Besançon, France: Presses Universitaires de Framche-Comté.
28. Niblack, W., Barber, R. Equitz, W., Flickner, M.D., Glasman, E.H., Petkovic D., et al. (1993). The QBIC project: Querying images by content using color, texture, and shape. Proceedings of the International Society for Optical Engineering (SPIE), 1908, 173-187.
29. Pastra, K. & Wilks, Y. (2004). Image-language multimodal corpora: Needs, lacunae, and an AI synergy for annotation. In Proceedings of the Language Resources and Evaluation Conference. (pp. 767-770).
30. Rafkind, B., Lee, M., Chang, S.E, &Yu, H. (2006). Exploring text and image features to classify images in bioscience literature. In Proceedings of the BioNLP Workshop on Linking Natural Language Processing and Biology at HLT-NAACL. (pp. 73-80).
31. Rius, S. (2006). Vers unereprésentation riche des images [Towards arich representation of images] Unpublished master's thesis. Institut de recherche en informatique et systémes aléatoires (IRISA), Rennes.
32. Robertson, S.E., Walker, S. & Beaulieu, M. (1998). OKAPI at TREC-7: Automatic Ad Hoc, Filtering, VLC, and Interactive. In Proceedings of the Seventh Text REtrieval Conference (TREC 7). (National Institute of Standards and Technology Special Publication 500-242, pp. 253-264). Gaithersburg, MD: NIST.
33. Rowe, N.C., & Guglielmo, E.J. (1993). Exploiting captions in retrieval of multimedia data. Information Processing & Management, 29, 453-461.
34. Ruiz, M.E., & Srikanth, M. (2004). UB at CLEF 2004: Part 2 cross language medical image retrieval. In Proceedings of the Cross-Language Evaluation Forum 2004 Workshop (pp. 773-780).
35. Shafkay, H., Chen, N., & Blostein, D. (2006). Integrating image data into biomedical text categorization. Bioinformatics, 22(14), e446-e453.
36. Smeulders, A.W, 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 & Machine Intelligence, 22, 1349-1380.
37. Srihari, R.K., Zhang, Z., & Rao, A. (2000). Intelligent indexing and semantic retrieval of multimodal documents. Information Retrieval, 2, 245-275.
38. Tamura, H., Mori, S., & Yamawaki, T. (1978). Textural features corresponding to visual perception. IEEE Transactions on Systems, Man, and Cybernetics, 8, 460-473.
39. Zhao, R., & Grosky, W. I. (2002). Narrowing the semantic gap: Improved text-based Web document retrieval using visual features. IEEE Transactions on Multimedia, 4, 189-200.