Model-Based Approach to Recognize the Rectus Abdominis Muscle in CT Images

DOI Web Site 被引用文献1件 参考文献12件 オープンアクセス
  • KAMIYA Naoki
    Department of Information and Computer Engineering, Toyota National College of Technology
  • ZHOU Xiangrong
    Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
  • CHEN Huayue
    Department of Anatomy, Graduate School of Medicine, Gifu University
  • MURAMATSU Chisako
    Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
  • HARA Takeshi
    Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University
  • FUJITA Hiroshi
    Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University

この論文をさがす

説明

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.

収録刊行物

被引用文献 (1)*注記

もっと見る

参考文献 (12)*注記

もっと見る

関連プロジェクト

もっと見る

キーワード

詳細情報 詳細情報について

問題の指摘

ページトップへ