書誌事項
- タイトル別名
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- Automatic fascia extraction and classification for measurement of muscle layer thickness
説明
<p>In this report, we proposed a method of classification of fascia and other tissue using Histograms of Oriented Gradients (HOG) and Support Vector Machine (SVM) in ultrasound images. The muscle layer can be determined by detecting the fascia. The decline of muscle and bone density due to aging is increased the likelihood of injury. So it is considered 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 analysis of ultrasound images. 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.</p>
収録刊行物
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- ロボティクス・メカトロニクス講演会講演概要集
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ロボティクス・メカトロニクス講演会講演概要集 2018 (0), 1A1-F05-, 2018
一般社団法人 日本機械学会
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詳細情報 詳細情報について
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- CRID
- 1390564238056913664
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- NII論文ID
- 130007551007
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- ISSN
- 24243124
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- Crossref
- CiNii Articles
- OpenAIRE
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- 抄録ライセンスフラグ
- 使用不可