2018年8月20日
Automatic fascia extraction and classification for measurement of muscle layer thickness
2018 15th International Conference on Ubiquitous Robots, UR 2018
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- 開始ページ
- 493
- 終了ページ
- 496
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/URAI.2018.8441877
- 出版者・発行元
- IEEE
In this report, we proposed a method of discriminating of fascia using Histograms of Oriented Gradients (HOG) and Support Vector Machine (SVM) in ultrasound images. In modern society, aging is progressing due to medical development. Along with that, the decline of muscle due to aging is regarded as a serious problem. To cope with this problem, we proposed a method of automatic fascia classification to visualize muscle thickness. Our method use SVM based on the texture of ultrasound images. In addition to this method, our method achieves about 90% Accuracy and Recall by considering that the fascia is a continuous tissue. Experimental results show the effectiveness of our proposed automatic fascia extraction method.
- リンク情報
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- DOI
- https://doi.org/10.1109/URAI.2018.8441877
- DBLP
- https://dblp.uni-trier.de/rec/conf/urai/ImaizumiKKNM18
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000447274600072&DestApp=WOS_CPL
- Scopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85053490503&origin=inward
- Scopus Citedby
- https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85053490503&origin=inward
- URL
- https://dblp.uni-trier.de/rec/conf/urai/2018
- URL
- https://dblp.uni-trier.de/db/conf/urai/urai2018.html#ImaizumiKKNM18
- ID情報
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- DOI : 10.1109/URAI.2018.8441877
- ISSN : 2325-033X
- ISBN : 9781538663349
- DBLP ID : conf/urai/ImaizumiKKNM18
- SCOPUS ID : 85053490503
- Web of Science ID : WOS:000447274600072