Augmented reality for botulinum toxin injection
Summary Augmented‐reality (AR) devices allow physicians to incorporate data visualization into diagnostic and treatment procedures to improve work efficiency and safety and reduce cost. They are also used to enhance surgical training. In this study, we implemented an AR application for Botox injecti...
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| Veröffentlicht in: | Concurrency and computation 2020-09, Vol.32 (18), p.n/a |
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| container_title | Concurrency and computation |
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| creator | Kim, HyoJoon Jeong, SangHui Seo, JiHyeon Park, InSeok Ko, Hoon Moon, Seong Yong |
| description | Summary
Augmented‐reality (AR) devices allow physicians to incorporate data visualization into diagnostic and treatment procedures to improve work efficiency and safety and reduce cost. They are also used to enhance surgical training. In this study, we implemented an AR application for Botox injections using a face recognition algorithm based on deep learning, and we evaluated the recognition accuracy of this application using 27 participants. The accuracy was around 3 mm for all parts of the facial region. The method of increasing surgical efficiency with AR is accurate enough to be used for surgery and provides great potential for further development. |
| doi_str_mv | 10.1002/cpe.5526 |
| format | Article |
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Augmented‐reality (AR) devices allow physicians to incorporate data visualization into diagnostic and treatment procedures to improve work efficiency and safety and reduce cost. They are also used to enhance surgical training. In this study, we implemented an AR application for Botox injections using a face recognition algorithm based on deep learning, and we evaluated the recognition accuracy of this application using 27 participants. The accuracy was around 3 mm for all parts of the facial region. The method of increasing surgical efficiency with AR is accurate enough to be used for surgery and provides great potential for further development.</description><identifier>ISSN: 1532-0626</identifier><identifier>EISSN: 1532-0634</identifier><identifier>DOI: 10.1002/cpe.5526</identifier><language>eng</language><publisher>Hoboken: Wiley Subscription Services, Inc</publisher><subject>Algorithms ; Augmented reality ; botulinum toxins ; clinical education ; Diagnostic systems ; Face recognition ; injection technique ; Machine learning ; Physicians ; Scientific visualization</subject><ispartof>Concurrency and computation, 2020-09, Vol.32 (18), p.n/a</ispartof><rights>2019 John Wiley & Sons, Ltd.</rights><rights>2020 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2936-7762536cb721c4579e1119a6d49297518595da80e4ee4b174600b755f34fd7103</citedby><cites>FETCH-LOGICAL-c2936-7762536cb721c4579e1119a6d49297518595da80e4ee4b174600b755f34fd7103</cites><orcidid>0000-0002-2386-2872 ; 0000-0001-6123-4810 ; 0000-0002-7513-4404 ; 0000-0002-4604-1735 ; 0000-0002-2081-8753</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fcpe.5526$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fcpe.5526$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Kim, HyoJoon</creatorcontrib><creatorcontrib>Jeong, SangHui</creatorcontrib><creatorcontrib>Seo, JiHyeon</creatorcontrib><creatorcontrib>Park, InSeok</creatorcontrib><creatorcontrib>Ko, Hoon</creatorcontrib><creatorcontrib>Moon, Seong Yong</creatorcontrib><title>Augmented reality for botulinum toxin injection</title><title>Concurrency and computation</title><description>Summary
Augmented‐reality (AR) devices allow physicians to incorporate data visualization into diagnostic and treatment procedures to improve work efficiency and safety and reduce cost. They are also used to enhance surgical training. In this study, we implemented an AR application for Botox injections using a face recognition algorithm based on deep learning, and we evaluated the recognition accuracy of this application using 27 participants. The accuracy was around 3 mm for all parts of the facial region. The method of increasing surgical efficiency with AR is accurate enough to be used for surgery and provides great potential for further development.</description><subject>Algorithms</subject><subject>Augmented reality</subject><subject>botulinum toxins</subject><subject>clinical education</subject><subject>Diagnostic systems</subject><subject>Face recognition</subject><subject>injection technique</subject><subject>Machine learning</subject><subject>Physicians</subject><subject>Scientific visualization</subject><issn>1532-0626</issn><issn>1532-0634</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNp10E1Lw0AQBuBFFKxV8CcEvHhJu7Of3WMJtQoFPeh5ycdENiTZuEnQ_ntTI948zRwe3hleQm6BroBSts47XEnJ1BlZgOQspoqL87-dqUty1fcVpQCUw4Kst-N7g-2ARRQwrd1wjEofoswPY-3asYkG_-XayLUV5oPz7TW5KNO6x5vfuSRvD7vX5DE-PO-fku0hzpnhKtZaMclVnmkGuZDaIACYVBXCMKMlbKSRRbqhKBBFBlooSjMtZclFWejptSW5m3O74D9G7Adb-TG000nLBFeKG2rUpO5nlQff9wFL2wXXpOFogdpTHXaqw57qmGg8009X4_FfZ5OX3Y__BnFGXho</recordid><startdate>20200925</startdate><enddate>20200925</enddate><creator>Kim, HyoJoon</creator><creator>Jeong, SangHui</creator><creator>Seo, JiHyeon</creator><creator>Park, InSeok</creator><creator>Ko, Hoon</creator><creator>Moon, Seong Yong</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0002-2386-2872</orcidid><orcidid>https://orcid.org/0000-0001-6123-4810</orcidid><orcidid>https://orcid.org/0000-0002-7513-4404</orcidid><orcidid>https://orcid.org/0000-0002-4604-1735</orcidid><orcidid>https://orcid.org/0000-0002-2081-8753</orcidid></search><sort><creationdate>20200925</creationdate><title>Augmented reality for botulinum toxin injection</title><author>Kim, HyoJoon ; Jeong, SangHui ; Seo, JiHyeon ; Park, InSeok ; Ko, Hoon ; Moon, Seong Yong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2936-7762536cb721c4579e1119a6d49297518595da80e4ee4b174600b755f34fd7103</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Augmented reality</topic><topic>botulinum toxins</topic><topic>clinical education</topic><topic>Diagnostic systems</topic><topic>Face recognition</topic><topic>injection technique</topic><topic>Machine learning</topic><topic>Physicians</topic><topic>Scientific visualization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, HyoJoon</creatorcontrib><creatorcontrib>Jeong, SangHui</creatorcontrib><creatorcontrib>Seo, JiHyeon</creatorcontrib><creatorcontrib>Park, InSeok</creatorcontrib><creatorcontrib>Ko, Hoon</creatorcontrib><creatorcontrib>Moon, Seong Yong</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Concurrency and computation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, HyoJoon</au><au>Jeong, SangHui</au><au>Seo, JiHyeon</au><au>Park, InSeok</au><au>Ko, Hoon</au><au>Moon, Seong Yong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Augmented reality for botulinum toxin injection</atitle><jtitle>Concurrency and computation</jtitle><date>2020-09-25</date><risdate>2020</risdate><volume>32</volume><issue>18</issue><epage>n/a</epage><issn>1532-0626</issn><eissn>1532-0634</eissn><abstract>Summary
Augmented‐reality (AR) devices allow physicians to incorporate data visualization into diagnostic and treatment procedures to improve work efficiency and safety and reduce cost. They are also used to enhance surgical training. In this study, we implemented an AR application for Botox injections using a face recognition algorithm based on deep learning, and we evaluated the recognition accuracy of this application using 27 participants. The accuracy was around 3 mm for all parts of the facial region. The method of increasing surgical efficiency with AR is accurate enough to be used for surgery and provides great potential for further development.</abstract><cop>Hoboken</cop><pub>Wiley Subscription Services, Inc</pub><doi>10.1002/cpe.5526</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-2386-2872</orcidid><orcidid>https://orcid.org/0000-0001-6123-4810</orcidid><orcidid>https://orcid.org/0000-0002-7513-4404</orcidid><orcidid>https://orcid.org/0000-0002-4604-1735</orcidid><orcidid>https://orcid.org/0000-0002-2081-8753</orcidid></addata></record> |
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| ispartof | Concurrency and computation, 2020-09, Vol.32 (18), p.n/a |
| issn | 1532-0626 1532-0634 |
| language | eng |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | Algorithms Augmented reality botulinum toxins clinical education Diagnostic systems Face recognition injection technique Machine learning Physicians Scientific visualization |
| title | Augmented reality for botulinum toxin injection |
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