Content-based image retrieval in picture archiving and communications systems.
We propose the concept of content-based image retrieval (CBIR) and demonstrate its potential use in picture archival and communication system (PACS). We address the importance of image retrieval in PACS and highlight the drawbacks existing in traditional textual-based retrieval. We use a digital mammogram database as our testing data to illustrate the idea of CBIR, where retrieval is carried out based on object shape, size, and brightness histogram. With a user-supplied query image, the system can find images with similar characteristics from the archive, and return them along with the corresponding ancillary data, which may provide a valuable reference for radiologists in a new case study. Furthermore, CBIR can perform like a consultant in emergencies when radiologists are not available. We also show that content-based retrieval is a more natural approach to man-machine communication.
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Center for Advanced Computing and Communication, North Carolina State University, Raleigh 27695-7914, USA.
Snyder
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D003253:Consultants; D019992:Databases as Topic; D003936:Diagnosis, Computer-Assisted; D003952:Diagnostic Imaging; D006801:Humans; D016247:Information Storage and Retrieval; D008327:Mammography; D008328:Man-Machine Systems; D010363:Pattern Recognition, Automated; D011873:Radiology Information Systems; D012016:Reference Values; D014584:User-Computer Interface