Model-Based Approach to Recognize the Rectus Abdominis Muscle in CT Images
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概要
- 論文の詳細を見る
Our purpose in this study is to develop a scheme to segment the rectus abdominis muscle region in X-ray CT images. We propose a new muscle recognition method based on the shape model. In this method, three steps are included in the segmentation process. The first is to generate a shape model for representing the rectus abdominis muscle. The second is to recognize anatomical feature points corresponding to the origin and insertion of the muscle, and the third is to segment the rectus abdominis muscles using the shape model. We generated the shape model from 20 CT cases and tested the model to recognize the muscle in 10 other CT cases. The average value of the Jaccard similarity coefficient (JSC) between the manually and automatically segmented regions was 0.843. The results suggest the validity of the model-based segmentation for the rectus abdominis muscle.
- The Institute of Electronics, Information and Communication Engineersの論文
著者
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Zhou Xiangrong
Department Of Intelligent Image Information Division Of Regeneration And Advanced Medical Science Gi
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Hara Takeshi
Department Of Animal Resource Sciences Graduate School Of Agricultural And Life Sciences The Univers
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Chen Huayue
Department Of Anatomy Division Of Disease Control Graduate School Of Medicine Gifu University
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Fujita Hiroshi
Department Of Applied Physics Faculty Of Engineering University Of Tokyo
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ZHOU Xiangrong
Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
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Kamiya NAOKI
Department of Gerontology, National Center for Geriatrics and Gerontology
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KAMIYA Naoki
Department of Information and Computer Engineering, Toyota National College of Technology
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MURAMATSU Chisako
Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
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HARA Takeshi
Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
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CHEN Huayue
Department of Anatomy, Graduate School of Medicine, Gifu University
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