title: Dicoogle, a PACS featuring profiled content based image retrieval.
abstract: Content-based image retrieval (CBIR) has been heralded as a mechanism to cope with the increasingly larger volumes of information present in medical imaging repositories. However, generic, extensible CBIR frameworks that work natively with Picture Archive and Communication Systems (PACS) are scarce. In this article we propose a methodology for parametric CBIR based on similarity profiles. The architecture and implementation of a profiled CBIR system, based on query by example, atop Dicoogle, an open-source, full-fletched PACS is also presented and discussed. In this solution, CBIR profiles allow the specification of both a distance function to be applied and the feature set that must be present for that function to operate. The presented framework provides the basis for a CBIR expansion mechanism and the solution developed integrates with DICOM based PACS networks where it provides CBIR functionality in a seamless manner.
authors.affiliation: IEETA, Universidade de Aveiro, Aveiro, Portugal. fmvalente@ua.pt
authors.forename: Frederico
authors.initials: F
authors.lastname: Valente
authors.forename: Carlos
authors.initials: C
authors.lastname: Costa
authors.forename: Augusto
authors.initials: A
authors.lastname: Silva
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted; D016247:Information Storage and Retrieval; D011859:Radiography; D011873:Radiology Information Systems; D012984:Software