Paper Abstract and Keywords |
Presentation |
2016-01-20 13:05
Application to whole CT images of automated recognition method of sternocleidomastoid muscle using atlas-based method Kosuke Ieda (Gifu Univ.), Naoki Kamiya (Aichi Pref. Univ.), Xiangrong Zhou, Megumi Yamada, Hiroki Kato, Chisako Muramatsu, Takeshi Hara, Toshiharu Miyoshi, Takashi Inuzuka, Masayuki Matsuo, Hiroshi Fujita (Gifu Univ.) MI2015-124 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The purpose of this research is to apply our previous method of automated recognition of a sternocleidomastoid muscle in torso CT images to whole-body CT images. While the imaging range of torso CT images was limited to the lower sternocleidomastoid muscle, whole sternocleidomastoid muscle is targeted in whole-body CT images. As with the previous method, we construct the average shape of the sternocleidomastoid muscle using the atlas. We improved the previous method on the alignment of the atlas to consider the extended imaging range. Therefore, the atlas is aligned using the outline shape of the sternocleidomastoid muscle. As a result, the average concordance rate was 60.3% using 10 cases of whole-body CT images with abnormalities in the skeletal muscles. We successfully recognized the major area of the sternocleidomastoid muscle well. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
ALS / CAD / Whole CT image / Skeletal muscle / Sternocleidomastoid muscle / / / |
Reference Info. |
IEICE Tech. Rep., vol. 115, no. 401, MI2015-124, pp. 247-250, Jan. 2016. |
Paper # |
MI2015-124 |
Date of Issue |
2016-01-12 (MI) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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MI2015-124 |
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