MACHINE-LEARNING-BASED VISUAL-HAPTIC FEEDBACK SYSTEM FOR ROBOTIC SURGICAL PLATFORMS
Embodiments described herein provide various examples of a machine-learning-based visual-haptic system for constructing visual-haptic models for various interactions between surgical tools and tissues. In one aspect, a process for constructing a visual-haptic model is disclosed. This process can beg...
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Patent |
| Sprache: | eng ; fre ; ger |
| 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 | VENKATARAMAN, Jagadish MILLER, Denise Ann |
| description | Embodiments described herein provide various examples of a machine-learning-based visual-haptic system for constructing visual-haptic models for various interactions between surgical tools and tissues. In one aspect, a process for constructing a visual-haptic model is disclosed. This process can begin by receiving a set of training videos. The process then processes each training video in the set of training videos to extract one or more video segments that depict a target tool-tissue interaction from the training video, wherein the target tool-tissue interaction involves exerting a force by one or more surgical tools on a tissue. Next, for each video segment in the set of video segments, the process annotates each video image in the video segment with a set of force levels predefined for the target tool-tissue interaction. The process subsequently trains a machine-learning model using the annotated video images to obtain a trained machine-learning model for the target tool-tissue interaction. |
| format | Patent |
| fullrecord | <record><control><sourceid>epo_EVB</sourceid><recordid>TN_cdi_epo_espacenet_EP3849452A4</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>EP3849452A4</sourcerecordid><originalsourceid>FETCH-epo_espacenet_EP3849452A43</originalsourceid><addsrcrecordid>eNrjZAj2dXT28PRz1fVxdQzy8_Rz13VyDHZ1UQjzDA519NH1cAwI8XRWcHN1dXFydPZWCI4MDnH1VXDzD1II8nfyB8kFhwa5ezo7-igE-DiGACV8g3kYWNMSc4pTeaE0NwPQgBBnD93Ugvz41OKCxOTUvNSSeNcAYwsTSxNTI0cTYyKUAACkGy-b</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>patent</recordtype></control><display><type>patent</type><title>MACHINE-LEARNING-BASED VISUAL-HAPTIC FEEDBACK SYSTEM FOR ROBOTIC SURGICAL PLATFORMS</title><source>esp@cenet</source><creator>VENKATARAMAN, Jagadish ; MILLER, Denise Ann</creator><creatorcontrib>VENKATARAMAN, Jagadish ; MILLER, Denise Ann</creatorcontrib><description>Embodiments described herein provide various examples of a machine-learning-based visual-haptic system for constructing visual-haptic models for various interactions between surgical tools and tissues. In one aspect, a process for constructing a visual-haptic model is disclosed. This process can begin by receiving a set of training videos. The process then processes each training video in the set of training videos to extract one or more video segments that depict a target tool-tissue interaction from the training video, wherein the target tool-tissue interaction involves exerting a force by one or more surgical tools on a tissue. Next, for each video segment in the set of video segments, the process annotates each video image in the video segment with a set of force levels predefined for the target tool-tissue interaction. The process subsequently trains a machine-learning model using the annotated video images to obtain a trained machine-learning model for the target tool-tissue interaction.</description><language>eng ; fre ; ger</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; 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 ; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ; MEDICAL OR VETERINARY SCIENCE ; PHYSICS ; SURGERY</subject><creationdate>2022</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=20220615&DB=EPODOC&CC=EP&NR=3849452A4$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,777,882,25545,76296</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20220615&DB=EPODOC&CC=EP&NR=3849452A4$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>VENKATARAMAN, Jagadish</creatorcontrib><creatorcontrib>MILLER, Denise Ann</creatorcontrib><title>MACHINE-LEARNING-BASED VISUAL-HAPTIC FEEDBACK SYSTEM FOR ROBOTIC SURGICAL PLATFORMS</title><description>Embodiments described herein provide various examples of a machine-learning-based visual-haptic system for constructing visual-haptic models for various interactions between surgical tools and tissues. In one aspect, a process for constructing a visual-haptic model is disclosed. This process can begin by receiving a set of training videos. The process then processes each training video in the set of training videos to extract one or more video segments that depict a target tool-tissue interaction from the training video, wherein the target tool-tissue interaction involves exerting a force by one or more surgical tools on a tissue. Next, for each video segment in the set of video segments, the process annotates each video image in the video segment with a set of force levels predefined for the target tool-tissue interaction. The process subsequently trains a machine-learning model using the annotated video images to obtain a trained machine-learning model for the target tool-tissue interaction.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</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>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>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZAj2dXT28PRz1fVxdQzy8_Rz13VyDHZ1UQjzDA519NH1cAwI8XRWcHN1dXFydPZWCI4MDnH1VXDzD1II8nfyB8kFhwa5ezo7-igE-DiGACV8g3kYWNMSc4pTeaE0NwPQgBBnD93Ugvz41OKCxOTUvNSSeNcAYwsTSxNTI0cTYyKUAACkGy-b</recordid><startdate>20220615</startdate><enddate>20220615</enddate><creator>VENKATARAMAN, Jagadish</creator><creator>MILLER, Denise Ann</creator><scope>EVB</scope></search><sort><creationdate>20220615</creationdate><title>MACHINE-LEARNING-BASED VISUAL-HAPTIC FEEDBACK SYSTEM FOR ROBOTIC SURGICAL PLATFORMS</title><author>VENKATARAMAN, Jagadish ; MILLER, Denise Ann</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_EP3849452A43</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; fre ; ger</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</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>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>VENKATARAMAN, Jagadish</creatorcontrib><creatorcontrib>MILLER, Denise Ann</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>VENKATARAMAN, Jagadish</au><au>MILLER, Denise Ann</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>MACHINE-LEARNING-BASED VISUAL-HAPTIC FEEDBACK SYSTEM FOR ROBOTIC SURGICAL PLATFORMS</title><date>2022-06-15</date><risdate>2022</risdate><abstract>Embodiments described herein provide various examples of a machine-learning-based visual-haptic system for constructing visual-haptic models for various interactions between surgical tools and tissues. In one aspect, a process for constructing a visual-haptic model is disclosed. This process can begin by receiving a set of training videos. The process then processes each training video in the set of training videos to extract one or more video segments that depict a target tool-tissue interaction from the training video, wherein the target tool-tissue interaction involves exerting a force by one or more surgical tools on a tissue. Next, for each video segment in the set of video segments, the process annotates each video image in the video segment with a set of force levels predefined for the target tool-tissue interaction. The process subsequently trains a machine-learning model using the annotated video images to obtain a trained machine-learning model for the target tool-tissue interaction.</abstract><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | |
| ispartof | |
| issn | |
| language | eng ; fre ; ger |
| recordid | cdi_epo_espacenet_EP3849452A4 |
| source | esp@cenet |
| subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS 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 INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEDICAL OR VETERINARY SCIENCE PHYSICS SURGERY |
| title | MACHINE-LEARNING-BASED VISUAL-HAPTIC FEEDBACK SYSTEM FOR ROBOTIC SURGICAL PLATFORMS |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-19T06%3A22%3A03IST&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=VENKATARAMAN,%20Jagadish&rft.date=2022-06-15&rft_id=info:doi/&rft_dat=%3Cepo_EVB%3EEP3849452A4%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 |