| Paper Abstract and Keywords |
| Presentation |
2007-01-27 11:10
An atlas-driven approach for automated recognition of liver structure in non-contrasted torso CT images
Xiangrong Zhou, Teruhiko Kitagawa, Suguru Kawajiri, Xuejun Zhang, Takeshi Hara, Hiroshi Fujita, Ryujiro Yokoyama, Hiroshi Kondo, Masayuki Kanematsu, Hiroaki Hoshi (Gifu Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In this paper, we propose an atlas-driven approach for fully-automated segmentation of liver region in non-contrast x-ray torso CT images. This approach was composed by two steps; one is automated estimation of the liver probability that show the location and density (CT number) of the liver in CT images. The probability of the liver on the spatial location was constructed by a number of CT scans in which the liver regions were pre-segmented manually. Another step is automated segmentation of liver region based on liver probability. The proposed approach was used for automated liver segmentation from a number of non-contrast CT images. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
multi-slice torso CT image / liver segmentation / probabilistic model / / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 106, no. 510, MI2006-178, pp. 81-82, Jan. 2007. |
| Paper # |
MI2006-178 |
| Date of Issue |
2007-01-20 (MI) |
| ISSN |
Print edition: ISSN 0913-5685 |
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