title: Automated recognition of the psoas major muscles on X-ray CT images.
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.
authors: 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
authors: N
authors: N
authors: Kamiya
authors: X
authors: X
authors: Zhou
authors: H
authors: H
authors: Chen
authors: T
authors: T
authors: Hara
authors: H
authors: H
authors: Hoshi
authors: R
authors: R
authors: Yokoyama
authors: M
authors: M
authors: Kanematsu
authors: H
authors: H
authors: Fujita
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001842:Bone and Bones / Q000473:pathology; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D003952:Diagnostic Imaging / Q000379:methods; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D016658:Psoas Muscles / Q000000981:diagnostic imaging*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014965:X-Rays