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Automated recognition of the psoas major muscles on X-ray CT images.
Kamiya, N; Zhou, X; Chen, H; Hara, T; Hoshi, H; Yokoyama, R; Kanematsu, M; Fujita, H.
Affiliation
  • Kamiya N; Department of Intelligent Image Information, Division of Regeneration and Advanced Medical Sciences, Graduate School of Medicine, Gifu University, Yanagido 1-1, Gifu 501-1194, Japan. kamiya@fjt.info.gifu-u.ac.jp
Article in En | MEDLINE | ID: mdl-19963589
ABSTRACT
The purpose of this study is to recognize the psoas major muscle on X-ray CT images. For this purpose, we propose a novel recognition method. The recognition process in this method involves three

steps:

the generation of a shape model for the psoas major muscle, recognition of anatomical points such as the origin and insertion, and the recognition of the psoas major muscles by the use of the shape model. We generated the shape model using 20 CT cases and tested the model for recognition in 20 other CT cases. The average Jaccard similarity coefficient (JSC) and reproducibility rate were 0.704 and 0.783, respectively. Experimental results indicate that our method was effective for a 2-D cross-sectional area (CSA) analysis.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pattern Recognition, Automated / Tomography, X-Ray Computed / Psoas Muscles Type of study: Diagnostic_studies / Prognostic_studies Limits: Female / Humans / Male Language: En Journal: Annu Int Conf IEEE Eng Med Biol Soc Year: 2009 Document type: Article Affiliation country: Japón

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pattern Recognition, Automated / Tomography, X-Ray Computed / Psoas Muscles Type of study: Diagnostic_studies / Prognostic_studies Limits: Female / Humans / Male Language: En Journal: Annu Int Conf IEEE Eng Med Biol Soc Year: 2009 Document type: Article Affiliation country: Japón
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