Paper Abstract and Keywords |
Presentation |
2013-01-24 13:10
Computer-aided Delineation of Lung Tumor Regions in Treatment Planning CT Images and PET/CT Images Using Localized Level Set Approach Ze Jin, Hidetaka Arimura, Yoshiyuki Shioyama (Kyushu Univ.), Jumpei Kuwazuru (Medipolis Proton Therapy and Research Center), Taiki Magome, Katsumasa Nakamura, Hiroshi Honda, Fukai Toyofuku, Hideki Hirata, Masayuki Sasaki (Kyushu Univ.) MI2012-71 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
[Purpose]
The purpose of this study was to develop an automated delineation method of lung tumor regions in treatment planning computed tomography (CT) images and positron emission tomography (PET)/CT images using a localized level set approach.
[Methods]
Six data sets of treatment planning CT and PET/CT images of lung cancer patients were selected for this study. The PET images were registered to the planning CT images by using an affine transformation matrix, which was the same transformation matrix derived from registration between the planning CT images and CT images of PET/CT images. The initial regions of the lung tumors were identified by thresholding the PET images at a certain standardized uptake value (SUV). We proposed a localized level set method (LLSM), which determines an optimum contour of the GTV region. For performance evaluation, we employed the Dice similarity coefficient (DSC), which denotes the degree of region similarity between the gold standard of the GTV contoured by radiation oncologists and the GTV region extracted by the proposed method.
[Results and Conclusion]
Our proposed method was applied to the six data sets, and reached an average DSC of 0.77. The proposed method may be useful for assisting treatment planners in delineation of the tumor region. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
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Reference Info. |
IEICE Tech. Rep., vol. 112, no. 411, MI2012-71, pp. 49-51, Jan. 2013. |
Paper # |
MI2012-71 |
Date of Issue |
2013-01-17 (MI) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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MI2012-71 |
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