Method and system for evaluating severity of diabetic foot ulcer based on artificial intelligence
The invention belongs to the field of diabetic foot evaluation, and particularly relates to a diabetic foot ulcer severity evaluation method and system based on artificial intelligence, and the method comprises the steps: data labeling, model construction, small target enhancement, iterative loop, l...
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 | LI CHUNYU PENG XUEMIN |
| description | The invention belongs to the field of diabetic foot evaluation, and particularly relates to a diabetic foot ulcer severity evaluation method and system based on artificial intelligence, and the method comprises the steps: data labeling, model construction, small target enhancement, iterative loop, label distribution, correction tuning and evaluation classification. According to the scheme, the lightweight target detection network based on the FCOS framework is constructed, and a feature pyramid network taking MobileNetV3 as a backbone network is adopted, so that the efficiency is improved, the time is shortened, and the calculation cost is reduced through the lightweight backbone network; a single-point headless face detector is adopted as a small target enhancement module to enhance the attention to a small target, so that the detection capability of the small target similar to diabetic foot ulcer is improved; prominent features are determined by adopting a label distribution strategy, and a center correctio |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_CN117994251A</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>CN117994251A</sourcerecordid><originalsourceid>FETCH-epo_espacenet_CN117994251A3</originalsourceid><addsrcrecordid>eNqNyjsOwjAQBcA0FAi4w3IAivARSokiEA1U9NHGfk5WMnZkbyLl9lBwAKppZlnwA9pHSxws5Tkr3uRiIkzsR1YJHWVMSKIzRUdWuIWK-Z6oNHqDRC1nWIqBOKk4McKeJCi8lw7BYF0sHPuMzc9Vsb1dX_V9hyE2yAMbBGhTP8vyXFXH_am8HP45HxpqPeU</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>Method and system for evaluating severity of diabetic foot ulcer based on artificial intelligence</title><source>esp@cenet</source><creator>LI CHUNYU ; PENG XUEMIN</creator><creatorcontrib>LI CHUNYU ; PENG XUEMIN</creatorcontrib><description>The invention belongs to the field of diabetic foot evaluation, and particularly relates to a diabetic foot ulcer severity evaluation method and system based on artificial intelligence, and the method comprises the steps: data labeling, model construction, small target enhancement, iterative loop, label distribution, correction tuning and evaluation classification. According to the scheme, the lightweight target detection network based on the FCOS framework is constructed, and a feature pyramid network taking MobileNetV3 as a backbone network is adopted, so that the efficiency is improved, the time is shortened, and the calculation cost is reduced through the lightweight backbone network; a single-point headless face detector is adopted as a small target enhancement module to enhance the attention to a small target, so that the detection capability of the small target similar to diabetic foot ulcer is improved; prominent features are determined by adopting a label distribution strategy, and a center correctio</description><language>chi ; eng</language><subject>CALCULATING ; COMPUTING ; COUNTING ; DIAGNOSIS ; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA ; HUMAN NECESSITIES ; HYGIENE ; IDENTIFICATION ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; MEDICAL OR VETERINARY SCIENCE ; PHYSICS ; SURGERY</subject><creationdate>2024</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=20240507&DB=EPODOC&CC=CN&NR=117994251A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,778,883,25547,76298</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240507&DB=EPODOC&CC=CN&NR=117994251A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LI CHUNYU</creatorcontrib><creatorcontrib>PENG XUEMIN</creatorcontrib><title>Method and system for evaluating severity of diabetic foot ulcer based on artificial intelligence</title><description>The invention belongs to the field of diabetic foot evaluation, and particularly relates to a diabetic foot ulcer severity evaluation method and system based on artificial intelligence, and the method comprises the steps: data labeling, model construction, small target enhancement, iterative loop, label distribution, correction tuning and evaluation classification. According to the scheme, the lightweight target detection network based on the FCOS framework is constructed, and a feature pyramid network taking MobileNetV3 as a backbone network is adopted, so that the efficiency is improved, the time is shortened, and the calculation cost is reduced through the lightweight backbone network; a single-point headless face detector is adopted as a small target enhancement module to enhance the attention to a small target, so that the detection capability of the small target similar to diabetic foot ulcer is improved; prominent features are determined by adopting a label distribution strategy, and a center correctio</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DIAGNOSIS</subject><subject>HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA</subject><subject>HUMAN NECESSITIES</subject><subject>HYGIENE</subject><subject>IDENTIFICATION</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</subject><subject>MEDICAL OR VETERINARY SCIENCE</subject><subject>PHYSICS</subject><subject>SURGERY</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyjsOwjAQBcA0FAi4w3IAivARSokiEA1U9NHGfk5WMnZkbyLl9lBwAKppZlnwA9pHSxws5Tkr3uRiIkzsR1YJHWVMSKIzRUdWuIWK-Z6oNHqDRC1nWIqBOKk4McKeJCi8lw7BYF0sHPuMzc9Vsb1dX_V9hyE2yAMbBGhTP8vyXFXH_am8HP45HxpqPeU</recordid><startdate>20240507</startdate><enddate>20240507</enddate><creator>LI CHUNYU</creator><creator>PENG XUEMIN</creator><scope>EVB</scope></search><sort><creationdate>20240507</creationdate><title>Method and system for evaluating severity of diabetic foot ulcer based on artificial intelligence</title><author>LI CHUNYU ; PENG XUEMIN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN117994251A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DIAGNOSIS</topic><topic>HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA</topic><topic>HUMAN NECESSITIES</topic><topic>HYGIENE</topic><topic>IDENTIFICATION</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS</topic><topic>MEDICAL OR VETERINARY SCIENCE</topic><topic>PHYSICS</topic><topic>SURGERY</topic><toplevel>online_resources</toplevel><creatorcontrib>LI CHUNYU</creatorcontrib><creatorcontrib>PENG XUEMIN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LI CHUNYU</au><au>PENG XUEMIN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Method and system for evaluating severity of diabetic foot ulcer based on artificial intelligence</title><date>2024-05-07</date><risdate>2024</risdate><abstract>The invention belongs to the field of diabetic foot evaluation, and particularly relates to a diabetic foot ulcer severity evaluation method and system based on artificial intelligence, and the method comprises the steps: data labeling, model construction, small target enhancement, iterative loop, label distribution, correction tuning and evaluation classification. According to the scheme, the lightweight target detection network based on the FCOS framework is constructed, and a feature pyramid network taking MobileNetV3 as a backbone network is adopted, so that the efficiency is improved, the time is shortened, and the calculation cost is reduced through the lightweight backbone network; a single-point headless face detector is adopted as a small target enhancement module to enhance the attention to a small target, so that the detection capability of the small target similar to diabetic foot ulcer is improved; prominent features are determined by adopting a label distribution strategy, and a center correctio</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | chi ; eng |
| recordid | cdi_epo_espacenet_CN117994251A |
| source | esp@cenet |
| subjects | CALCULATING COMPUTING COUNTING DIAGNOSIS HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA HUMAN NECESSITIES HYGIENE IDENTIFICATION IMAGE DATA PROCESSING OR GENERATION, IN GENERAL INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEDICAL OR VETERINARY SCIENCE PHYSICS SURGERY |
| title | Method and system for evaluating severity of diabetic foot ulcer based on artificial intelligence |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T17%3A56%3A20IST&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=LI%20CHUNYU&rft.date=2024-05-07&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3ECN117994251A%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 |