Extending relational databases to support content-based retrieval of medical images

This paper shows how to support images in a relational database, so it can fulfill the requirements to be used as the storage mechanism of a PACS. This support includes the ability to answer similarity queries based on the image content, providing fast image retrieval based on indexing structures. The main concept allowing this support is the definition of distance functions based on features, which are extracted from the images as they are stored in the database. An extension to SQL enables the construction of an interpreter that intercepts the extended commands and translates them into standard SQL, allowing one to take advantage of any relational database server. We describe experiments made with a prototype implemented using these concepts, which allowed answering queries up to 20 times faster than using existing relational servers alone.

[1]  Xinhua Cao,et al.  Current status and future advances of digital radiography and PACS , 2000, IEEE Engineering in Medicine and Biology Magazine.

[2]  Jorge Muniz Barreto,et al.  CT scans with neurocysticercosis in epileptics patients: a computer-based method for detection and quantification , 1999, Proceedings 12th IEEE Symposium on Computer-Based Medical Systems (Cat. No.99CB36365).

[3]  Marcel Worring,et al.  Content-Based Image Retrieval at the End of the Early Years , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  David L. Reich,et al.  Linking clinical, research and administrative computer systems , 2000, Proceedings 13th IEEE Symposium on Computer-Based Medical Systems. CBMS 2000.

[5]  Agma J. M. Traina,et al.  The Metric Histogram: A New and Efficient Approach for Content-based Image Retrieval , 2002, VDB.

[6]  Roberto Brunelli,et al.  On the use of histograms for image retrieval , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[7]  Christos Faloutsos,et al.  Fast Indexing and Visualization of Metric Data Sets using Slim-Trees , 2002, IEEE Trans. Knowl. Data Eng..