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.
Highlights
Radiology requires a careful interpretation of the signals present in medical images in order to provide an accurate diagnosis
But after the move of the imaging technologies to a digital medium, radiology has become a prevalent specialty throughout most health-care institutions
In this article we propose a methodology, and discuss a working implementation, for a profile-based Content-based image retrieval (CBIR) system aimed at Picture Archive and Communication Systems (PACS) networks
Summary
Radiology requires a careful interpretation of the signals present in medical images in order to provide an accurate diagnosis. But after the move of the imaging technologies to a digital medium, radiology has become a prevalent specialty throughout most health-care institutions. During 2006, around 50000 images were produced per day in large medical institutions [1] This rapid increase in collected data, known as ‘‘data explosion’’, is a recent phenomenon and was made possible due to both the capacity increments of the storage devices and the technological breakthroughs on imaging modalities. Nowadays, such modalities can very quickly produce images of unprecedented resolution and detail [2]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
