Open Access
Description:
Large amounts of medical visual data are produced daily in hospitals, while new imaging techniques continue to emerge. In addition, many images are made available continuously via publications in the scientific literature and can also be valuable for clinical routine, research and education. Information retrieval systems are useful tools to provide access to the biomedical literature and fulfil the information needs of medical professionals. The tools developed in this thesis can potentially help clinicians make decisions about difficult diagnoses via a case-based retrieval system based on a use case associated with a specific evaluation task. This system retrieves articles from the biomedical literature when querying with a case description and attached images. This thesis proposes a multimodal approach for medical case-based retrieval with focus on the integration of visual information connected to text. Furthermore, the ImageCLEFmed evaluation campaign was organised during this thesis promoting medical retrieval system evaluation.
Publisher:
Université de Genève
Contributors:
Muller, Henning ; Marchand-Maillet, Stéphane
Year of Publication:
2015
Document Type:
info:eu-repo/semantics/doctoralThesis ; Dissertation ; Thèse ; [Doctoral and postdoctoral thesis]
Language:
eng
Subjects:
info:eu-repo/classification/ddc/025.063 ; info:eu-repo/classification/ddc/616.0757 ; Medical visual information retrieval ; System evaluation ; Use case ; ImageCLEF ; Medical case retrieval ; Query adaptive multi-modal fusion ; Shangri-la ; Classification ; Training set expansion
Rights:
info:eu-repo/semantics/openAccess
Relations:
info:eu-repo/grantAgreement/EC/FP7//EU/KHRESMOI/ ; info:eu-repo/grantAgreement/EC/FP7//EU/PROMISE/ ; unige:73184
Content Provider:
Université de Genève: Archive ouverte UNIGE  Flag of Switzerland
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