DocumentCode
2505474
Title
Automated segmentation of recuts abdominis muscle using shape model in X-ray CT images
Author
Kamiya, N. ; Zhou, X. ; Chen, H. ; Muramatsu, C. ; Hara, T. ; Yokoyama, R. ; Kanematsu, M. ; Hoshi, H. ; Fujita, H.
Author_Institution
Dept. of Intell. Image Inf., Gifu Univ., Gifu, Japan
fYear
2011
fDate
Aug. 30 2011-Sept. 3 2011
Firstpage
7993
Lastpage
7996
Abstract
Our purpose in this study is to segment the rectus abdominis muscle region in X-ray CT images, and we propose a novel 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 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 based on the shape model. We generated the shape model from 20 CT cases and tested the model to recognize the muscle in 20 other CT cases. The average values for the Jaccard similarity coefficient (JSC) and true segmentation coefficient (TSC) were 0.841 and 0.863, respectively. The results suggest the validity of the model-based segmentation for the rectus abdominis muscle.
Keywords
computerised tomography; image segmentation; medical image processing; muscle; Jaccard similarity coefficient; X-ray CT images; anatomical feature points; automated segmentation; rectus abdominis muscle; shape model; true segmentation coefficient; Computed tomography; Image recognition; Image segmentation; Muscles; Shape; Solid modeling; Torso; Automation; Humans; Imaging, Three-Dimensional; Models, Anatomic; Radiographic Image Interpretation, Computer-Assisted; Rectus Abdominis; Tomography, X-Ray Computed;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location
Boston, MA
ISSN
1557-170X
Print_ISBN
978-1-4244-4121-1
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2011.6091971
Filename
6091971
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