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. T...
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 308 |
|---|---|
| container_issue | |
| container_start_page | 303 |
| container_title | |
| container_volume | |
| creator | Araujo, M.R.B. Traina, C. Traina, A. Bueno, J.M. Razente, H.L. |
| description | 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. |
| doi_str_mv | 10.1109/CBMS.2002.1011393 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_1011393</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>1011393</ieee_id><sourcerecordid>1011393</sourcerecordid><originalsourceid>FETCH-LOGICAL-i204t-3c96c7194929d1c22d9fad9f99ed99814a50c7e35b887c78399952cadfaca86a3</originalsourceid><addsrcrecordid>eNotkNFKAzEQRQMqWGs_QHzZH9iaSTbJzqMutQoVH6rPZZpkS2S7u2yi6N8bsQPDvXAPc2EYuwG-BOB41zy8bJeCc7EEDiBRnrErbjQq0FDhOZsB17I0INQlW8T4wfMorlHDjG1X38n3LvSHYvIdpTD01BWOEu0p-likoYif4zhMqbBDn9FU_gUu02kK_ivDQ1scvQs223Ckg4_X7KKlLvrFSefs_XH11jyVm9f1c3O_KYPgVSqlRW0NYIUCHVghHLaUF9E7xBoqUtwaL9W-ro01tUREJSy5lizVmuSc3f7fDd773Tjl9ulnd_qB_AXu-1Ey</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Extending relational databases to support content-based retrieval of medical images</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Araujo, M.R.B. ; Traina, C. ; Traina, A. ; Bueno, J.M. ; Razente, H.L.</creator><creatorcontrib>Araujo, M.R.B. ; Traina, C. ; Traina, A. ; Bueno, J.M. ; Razente, H.L.</creatorcontrib><description>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.</description><identifier>ISSN: 1063-7125</identifier><identifier>ISBN: 0769516149</identifier><identifier>ISBN: 9780769516141</identifier><identifier>DOI: 10.1109/CBMS.2002.1011393</identifier><language>eng</language><publisher>IEEE</publisher><subject>Biomedical imaging ; Content based retrieval ; Feature extraction ; Image databases ; Image retrieval ; Image storage ; Indexing ; Information retrieval ; Picture archiving and communication systems ; Relational databases</subject><ispartof>Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002), 2002, p.303-308</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1011393$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,4036,4037,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1011393$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Araujo, M.R.B.</creatorcontrib><creatorcontrib>Traina, C.</creatorcontrib><creatorcontrib>Traina, A.</creatorcontrib><creatorcontrib>Bueno, J.M.</creatorcontrib><creatorcontrib>Razente, H.L.</creatorcontrib><title>Extending relational databases to support content-based retrieval of medical images</title><title>Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002)</title><addtitle>CBMS</addtitle><description>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.</description><subject>Biomedical imaging</subject><subject>Content based retrieval</subject><subject>Feature extraction</subject><subject>Image databases</subject><subject>Image retrieval</subject><subject>Image storage</subject><subject>Indexing</subject><subject>Information retrieval</subject><subject>Picture archiving and communication systems</subject><subject>Relational databases</subject><issn>1063-7125</issn><isbn>0769516149</isbn><isbn>9780769516141</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2002</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkNFKAzEQRQMqWGs_QHzZH9iaSTbJzqMutQoVH6rPZZpkS2S7u2yi6N8bsQPDvXAPc2EYuwG-BOB41zy8bJeCc7EEDiBRnrErbjQq0FDhOZsB17I0INQlW8T4wfMorlHDjG1X38n3LvSHYvIdpTD01BWOEu0p-likoYif4zhMqbBDn9FU_gUu02kK_ivDQ1scvQs223Ckg4_X7KKlLvrFSefs_XH11jyVm9f1c3O_KYPgVSqlRW0NYIUCHVghHLaUF9E7xBoqUtwaL9W-ro01tUREJSy5lizVmuSc3f7fDd773Tjl9ulnd_qB_AXu-1Ey</recordid><startdate>2002</startdate><enddate>2002</enddate><creator>Araujo, M.R.B.</creator><creator>Traina, C.</creator><creator>Traina, A.</creator><creator>Bueno, J.M.</creator><creator>Razente, H.L.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2002</creationdate><title>Extending relational databases to support content-based retrieval of medical images</title><author>Araujo, M.R.B. ; Traina, C. ; Traina, A. ; Bueno, J.M. ; Razente, H.L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i204t-3c96c7194929d1c22d9fad9f99ed99814a50c7e35b887c78399952cadfaca86a3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Biomedical imaging</topic><topic>Content based retrieval</topic><topic>Feature extraction</topic><topic>Image databases</topic><topic>Image retrieval</topic><topic>Image storage</topic><topic>Indexing</topic><topic>Information retrieval</topic><topic>Picture archiving and communication systems</topic><topic>Relational databases</topic><toplevel>online_resources</toplevel><creatorcontrib>Araujo, M.R.B.</creatorcontrib><creatorcontrib>Traina, C.</creatorcontrib><creatorcontrib>Traina, A.</creatorcontrib><creatorcontrib>Bueno, J.M.</creatorcontrib><creatorcontrib>Razente, H.L.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Araujo, M.R.B.</au><au>Traina, C.</au><au>Traina, A.</au><au>Bueno, J.M.</au><au>Razente, H.L.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Extending relational databases to support content-based retrieval of medical images</atitle><btitle>Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002)</btitle><stitle>CBMS</stitle><date>2002</date><risdate>2002</risdate><spage>303</spage><epage>308</epage><pages>303-308</pages><issn>1063-7125</issn><isbn>0769516149</isbn><isbn>9780769516141</isbn><abstract>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.</abstract><pub>IEEE</pub><doi>10.1109/CBMS.2002.1011393</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISSN: 1063-7125 |
| ispartof | Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002), 2002, p.303-308 |
| issn | 1063-7125 |
| language | eng |
| recordid | cdi_ieee_primary_1011393 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Biomedical imaging Content based retrieval Feature extraction Image databases Image retrieval Image storage Indexing Information retrieval Picture archiving and communication systems Relational databases |
| title | Extending relational databases to support content-based retrieval of medical images |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-11T16%3A37%3A52IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Extending%20relational%20databases%20to%20support%20content-based%20retrieval%20of%20medical%20images&rft.btitle=Proceedings%20of%2015th%20IEEE%20Symposium%20on%20Computer-Based%20Medical%20Systems%20(CBMS%202002)&rft.au=Araujo,%20M.R.B.&rft.date=2002&rft.spage=303&rft.epage=308&rft.pages=303-308&rft.issn=1063-7125&rft.isbn=0769516149&rft.isbn_list=9780769516141&rft_id=info:doi/10.1109/CBMS.2002.1011393&rft_dat=%3Cieee_6IE%3E1011393%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=1011393&rfr_iscdi=true |