Paper Abstract and Keywords |
Presentation |
2013-11-07 16:20
Mediastinal Lymph Node Detection Method Based on Radial Structure Tensor and Machine Learning Hirohisa Oda, Xiongbiao Luo, Yukitaka Nimura, Masahiro Oda (Nagoya Univ.), Takayuki Kitasaka (Aichi Inst. of Tech.), Shingo Iwano (Nagoya Univ.), Hirotoshi Honma (Sapporo Kosei Hospital), Hirotsugu Takabatake (Sapporo Minami-sanjo Hospital), Masaki Mori (Sapporo Kosei Hospital), Hiroshi Natori (Keiwakai Nishioka Hospital), Kensaku Mori (Nagoya Univ.) MI2013-55 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In this paper, we present a method for detecting mediastinal lymph nodes from 3D chest CT volumes. Mediastinal lymph nodes are observed as blob structures which have higher CT values than the surrounding regions. However, there are lymph nodes adhering other tissue and tissue which have as high CT value as lymph nodes. In the proposed method, a blobness structure enhancement filter based on Radial Structure Tensor (R-BSE) is utilized to obtain candidate regions because the R-BSE is robust for influence of neighboring tissues. The candidate regions are classified into lymph nodes and others by the support vector machine. Shape, location, and CT value of candidate regions are used as feature values. We applied the proposed method to 46 cases of arterial phase 3D CT volumes. The method detected 85.6 % of lymph nodes whose minor axis is no less than 5.0 [mm] with 14.9 FP(False Positive)s per patient. The method also detected 88.5 % of lymph nodes whose minor axis is no less than 10.0 [mm] with 14.8 FPs per patient. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
CAD / Lung Cancer / Support Vector Machine / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 113, no. 281, MI2013-55, pp. 51-56, Nov. 2013. |
Paper # |
MI2013-55 |
Date of Issue |
2013-10-31 (MI) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
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MI2013-55 |
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