Model-based differential diagnosis of dementia and interactive setting of level of significance
When detecting and classifying hypo-metabolic regions in the brain to facilitate dementia diagnosis, a patient's brain scan image, generated using an FDG-PET scan, is compared to a plurality of hypo-metabolic region patterns in brain scan images associated with a plurality of types of dementia....
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Patent |
| Sprache: | chi ; eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | BUCHERT RALPH THIELE FRANK O YOUNG STEWART M VIK TORBJOERN WENZEL FABIAN |
| description | When detecting and classifying hypo-metabolic regions in the brain to facilitate dementia diagnosis, a patient's brain scan image, generated using an FDG-PET scan, is compared to a plurality of hypo-metabolic region patterns in brain scan images associated with a plurality of types of dementia. In a fully automated mode, the patient's scan is compared to all scans stored in a knowledge base, and atype of dementia associated with a most likely match is output to a user along with a highlighted image of the patient' s brain. In a semi-automated mode, a user specifies two or more types of dementia, and the patient's scan is compared to scans typical of the specified types. Diagnosis information including respective likelihoods for each type is then output to the user. Additionally, the usercan adjust a threshold significance level to increase or decrease a number of voxels that are included in hypo-metabolic regions highlighted in the patient' s brain scan image. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN101681515A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN101681515A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN101681515A3</originalsourceid><addsrcrecordid>eNqNikEKwjAQRbNxIeod4gEKBqm4laK40ZX7MCY_ZSBOSif0_FrxAK7ef5-3NP5WInLzJEW0kVPCCKlM-SPUS1FWW5KNeH1vSxItS8VIofIEq6iVpZ-bjAl5Hsq9cOJAErA2i0RZsflxZbaX86O7NhiKhw4UIKi-u7udOxxd69rT_p_mDYVFPPk</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Model-based differential diagnosis of dementia and interactive setting of level of significance</title><source>esp@cenet</source><creator>BUCHERT RALPH ; THIELE FRANK O ; YOUNG STEWART M ; VIK TORBJOERN ; WENZEL FABIAN</creator><creatorcontrib>BUCHERT RALPH ; THIELE FRANK O ; YOUNG STEWART M ; VIK TORBJOERN ; WENZEL FABIAN</creatorcontrib><description>When detecting and classifying hypo-metabolic regions in the brain to facilitate dementia diagnosis, a patient's brain scan image, generated using an FDG-PET scan, is compared to a plurality of hypo-metabolic region patterns in brain scan images associated with a plurality of types of dementia. In a fully automated mode, the patient's scan is compared to all scans stored in a knowledge base, and atype of dementia associated with a most likely match is output to a user along with a highlighted image of the patient' s brain. In a semi-automated mode, a user specifies two or more types of dementia, and the patient's scan is compared to scans typical of the specified types. Diagnosis information including respective likelihoods for each type is then output to the user. Additionally, the usercan adjust a threshold significance level to increase or decrease a number of voxels that are included in hypo-metabolic regions highlighted in the patient' s brain scan image.</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; PHYSICS</subject><creationdate>2010</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20100324&DB=EPODOC&CC=CN&NR=101681515A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76289</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20100324&DB=EPODOC&CC=CN&NR=101681515A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>BUCHERT RALPH</creatorcontrib><creatorcontrib>THIELE FRANK O</creatorcontrib><creatorcontrib>YOUNG STEWART M</creatorcontrib><creatorcontrib>VIK TORBJOERN</creatorcontrib><creatorcontrib>WENZEL FABIAN</creatorcontrib><title>Model-based differential diagnosis of dementia and interactive setting of level of significance</title><description>When detecting and classifying hypo-metabolic regions in the brain to facilitate dementia diagnosis, a patient's brain scan image, generated using an FDG-PET scan, is compared to a plurality of hypo-metabolic region patterns in brain scan images associated with a plurality of types of dementia. In a fully automated mode, the patient's scan is compared to all scans stored in a knowledge base, and atype of dementia associated with a most likely match is output to a user along with a highlighted image of the patient' s brain. In a semi-automated mode, a user specifies two or more types of dementia, and the patient's scan is compared to scans typical of the specified types. Diagnosis information including respective likelihoods for each type is then output to the user. Additionally, the usercan adjust a threshold significance level to increase or decrease a number of voxels that are included in hypo-metabolic regions highlighted in the patient' s brain scan image.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2010</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNikEKwjAQRbNxIeod4gEKBqm4laK40ZX7MCY_ZSBOSif0_FrxAK7ef5-3NP5WInLzJEW0kVPCCKlM-SPUS1FWW5KNeH1vSxItS8VIofIEq6iVpZ-bjAl5Hsq9cOJAErA2i0RZsflxZbaX86O7NhiKhw4UIKi-u7udOxxd69rT_p_mDYVFPPk</recordid><startdate>20100324</startdate><enddate>20100324</enddate><creator>BUCHERT RALPH</creator><creator>THIELE FRANK O</creator><creator>YOUNG STEWART M</creator><creator>VIK TORBJOERN</creator><creator>WENZEL FABIAN</creator><scope>EVB</scope></search><sort><creationdate>20100324</creationdate><title>Model-based differential diagnosis of dementia and interactive setting of level of significance</title><author>BUCHERT RALPH ; THIELE FRANK O ; YOUNG STEWART M ; VIK TORBJOERN ; WENZEL FABIAN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN101681515A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2010</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>BUCHERT RALPH</creatorcontrib><creatorcontrib>THIELE FRANK O</creatorcontrib><creatorcontrib>YOUNG STEWART M</creatorcontrib><creatorcontrib>VIK TORBJOERN</creatorcontrib><creatorcontrib>WENZEL FABIAN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>BUCHERT RALPH</au><au>THIELE FRANK O</au><au>YOUNG STEWART M</au><au>VIK TORBJOERN</au><au>WENZEL FABIAN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Model-based differential diagnosis of dementia and interactive setting of level of significance</title><date>2010-03-24</date><risdate>2010</risdate><abstract>When detecting and classifying hypo-metabolic regions in the brain to facilitate dementia diagnosis, a patient's brain scan image, generated using an FDG-PET scan, is compared to a plurality of hypo-metabolic region patterns in brain scan images associated with a plurality of types of dementia. In a fully automated mode, the patient's scan is compared to all scans stored in a knowledge base, and atype of dementia associated with a most likely match is output to a user along with a highlighted image of the patient' s brain. In a semi-automated mode, a user specifies two or more types of dementia, and the patient's scan is compared to scans typical of the specified types. Diagnosis information including respective likelihoods for each type is then output to the user. Additionally, the usercan adjust a threshold significance level to increase or decrease a number of voxels that are included in hypo-metabolic regions highlighted in the patient' s brain scan image.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN101681515A |
| source | esp@cenet |
| subjects | CALCULATING COMPUTING COUNTING IMAGE DATA PROCESSING OR GENERATION, IN GENERAL PHYSICS |
| title | Model-based differential diagnosis of dementia and interactive setting of level of significance |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T17%3A29%3A18IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-epo_EVB&rft_val_fmt=info:ofi/fmt:kev:mtx:patent&rft.genre=patent&rft.au=BUCHERT%20RALPH&rft.date=2010-03-24&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN101681515A%3C/epo_EVB%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |