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27 February 2009 Algorithm for lung cancer detection based on PET/CT images
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Proceedings Volume 7260, Medical Imaging 2009: Computer-Aided Diagnosis; 726034 (2009)
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
The five year survival rate of the lung cancer is low with about twenty-five percent. In addition it is an obstinate lung cancer wherein three out of four people die within five years. Then, the early stage detection and treatment of the lung cancer are important. Recently, we can obtain CT and PET image at the same time because PET/CT device has been developed. PET/CT is possible for a highly accurate cancer diagnosis because it analyzes quantitative shape information from CT image and FDG distribution from PET image. However, neither benign-malignant classification nor staging intended for lung cancer have been established still enough by using PET/CT images. In this study, we detect lung nodules based on internal organs extracted from CT image, and we also develop algorithm which classifies benignmalignant and metastatic or non metastatic lung cancer using lung structure and FDG distribution(one and two hour after administering FDG). We apply the algorithm to 59 PET/CT images (malignant 43 cases [Ad:31, Sq:9, sm:3], benign 16 cases) and show the effectiveness of this algorithm.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Shinsuke Saita, Keita Ishimatsu, Mitsuru Kubo, Yoshiki Kawata, Noboru Niki, Hideki Ohtsuka, Hiromu Nishitani, Hironobu Ohmatsu, Kenji Eguchi, Masahiro Kaneko, and Noriyuki Moriyama "Algorithm for lung cancer detection based on PET/CT images", Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 726034 (27 February 2009);

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