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19 May 2003 PACS archive server database structure enabling flexible queries
Sam Zhongmin Shen, Martin Joel Yaffe, Zhongming Chen, Gordon E. Mawdsley
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Proceedings Volume 5033, Medical Imaging 2003: PACS and Integrated Medical Information Systems: Design and Evaluation; (2003) https://doi.org/10.1117/12.480461
Event: Medical Imaging 2003, 2003, San Diego, California, United States
Abstract
An innovative DICOM meta information database has been developed to support PACS archive servers. Contrary to mainstream designs using a relational database with one table for each information level (namely: patient, study, series, image), we present a boolean-based design that supports the same information model with one table. In this table, the data are stored with the DICOM tags and auxiliary indices required for the information model. Each representative value in a DICOM data set is stored as a record in the table. When a new SOP Class is added, it is unnecessary to rebuild the entire database because no new columns are needed in the table. The new tag, i.e. new information, is added into the table as an additional record. With our current implementation of this model, the same query is typically almost as fast as the 4-table design. In tests using simulated data with a server holding 10,000 patients, each with 2 studies and 2 series of images, it takes less than 6 seconds to query all the patient names starting with “B” on our new database. It takes 5 seconds on a comparable server using the 4 table design. Searching for a value at image level requires a similar amount of time, depending on the amount of data returned.
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Sam Zhongmin Shen, Martin Joel Yaffe, Zhongming Chen, and Gordon E. Mawdsley "PACS archive server database structure enabling flexible queries", Proc. SPIE 5033, Medical Imaging 2003: PACS and Integrated Medical Information Systems: Design and Evaluation, (19 May 2003); https://doi.org/10.1117/12.480461
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KEYWORDS
Databases
Picture Archiving and Communication System
Data modeling
Image filtering
Molybdenum
Medical imaging
Statistical modeling
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