Paper Abstract and Keywords |
Presentation |
2019-01-23 14:00
[Short Paper]
A Lung Cancer Risk Prediction Model based on Clinical Information and Chest CT Images Analyses Takeru Kageyama, Yoshiki Kawata, Noboru Niki (Tokushima Univ.), Masahiko Kusumoto (National Cancer Center), Hironobu Ohmatsu (Abashiri Prison), Yoshiki Aokage, Takaaki Tsuchida, Yuji Matsumoto (National Cancer Center), Kenji Eguchi (Teikyo Univ.), Masahiro Kaneko (Tokyo Health Service Association Health Support Center) MI2018-98 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Lung cancer accounts for the number of cancer deaths first, and it is on an increasing trend. Although lung cancer CT screening that discovers lung cancer candidates using chest 3-dimensional CT images has been carried out recently as one of the methods for early detection of lung cancer, unnecessary definitive diagnosis is being carried out to non-cancer samples of 20 to 55%. In order to reduce the false positive rate of lung cancer in lung cancer CT screening, multiple malignant risk models have been published that categorize and score nodules in various countries around the world. In this study, we develop high-performance malignant risk models using clinical information and the results of image analysis of Japanese thin section CT images. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Lung nodule / Chest Chest 3-dimensional CT images / multiple malignant risk model / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 118, no. 412, MI2018-98, pp. 161-163, Jan. 2019. |
Paper # |
MI2018-98 |
Date of Issue |
2019-01-15 (MI) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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MI2018-98 |
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