Integrating user preference to similarity queries over medical images datasets

Autor: Marcelo Ponciano-Silva, Fabíola S. F. Pereira, Richard Chbeir, Agma J. M. Traina, Caetano Traina, Mônica Ribeiro Porto Ferreira, Sandra de Amo
Přispěvatelé: Chbeir, Richard, Data Bases and Images Group ( GBDI ), Universidade de São Paulo ( USP ), Faculdade de Computação, Universidade Federal de Uberlândia - UFU, Laboratoire Electronique, Informatique et Image ( Le2i ), Université de Bourgogne ( UB ) -AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique ( CNRS ), Data Bases and Images Group (GBDI), Universidade de São Paulo (USP), Laboratoire Electronique, Informatique et Image [UMR6306] (Le2i), Université de Bourgogne (UB)-École Nationale Supérieure d'Arts et Métiers (ENSAM), Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-Arts et Métiers Sciences et Technologies, HESAM Université (HESAM)-HESAM Université (HESAM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2010
Předmět:
[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]
[INFO.INFO-WB] Computer Science [cs]/Web
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
[ INFO.INFO-WB ] Computer Science [cs]/Web
[SCCO.COMP]Cognitive science/Computer science
Computed tomography
02 engineering and technology
Content-based image retrieval
Semantics
Image (mathematics)
Similarity (network science)
[SCCO.COMP] Cognitive science/Computer science
020204 information systems
0202 electrical engineering
electronic engineering
information engineering
medicine
[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]
Image retrieval
[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM]
[INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]
Information retrieval
[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]
medicine.diagnostic_test
[INFO.INFO-WB]Computer Science [cs]/Web
[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]
020207 software engineering
Preference
Important research
[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]
[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]
[ SCCO.COMP ] Cognitive science/Computer science
[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]
Zdroj: CBMS '10 Proceedings of the 2010 IEEE 23rd International Symposium on Computer-Based Medical Systems
CBMS '10 Proceedings of the 2010 IEEE 23rd International Symposium on Computer-Based Medical Systems, Oct 2010, Perth, Australia. pp.486-491, 〈http://dx.doi.org/10.1109/CBMS.2010.6042693〉
CBMS '10 Proceedings of the 2010 IEEE 23rd International Symposium on Computer-Based Medical Systems, Oct 2010, Perth, Australia. pp.486-491
CBMS
DOI: 10.1109/CBMS.2010.6042693〉
Popis: International audience; Large amounts of images from medical exams are being stored in databases, so developing retrieval techniques is an important research problem. Retrieval based on the image visual content is usually better than using textual descriptions, as they seldom gives every nuances that the user may be interested in. Content-based image retrieval employs the similarity among images for retrieval. However, similarity is evaluated using numeric methods, and they often orders the images by similarity in a way rather distinct from the user's intention. In this paper, we propose a technique to allow expressing the user's preference over attributes associated to the images, so similarity queries can be refined by preference rules. Experiments performed over a dataset with computed tomography lung images shows that correctly expressing the user's preferences, the similarity query precision can increase from an average of 60% up to close to 100%, when enough interesting images exists in the database.
Databáze: OpenAIRE
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