2017年8月29日
Detection of slices including a ground-glass opacity nodule in CT volume data with semi-supervised learning
Proceedings - 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2017
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- 開始ページ
- 557
- 終了ページ
- 561
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/SNPD.2017.8022778
- 出版者・発行元
- Institute of Electrical and Electronics Engineers Inc.
The features of GGO nodules need to be obtained such as volume, mean, variance of Ground-Glass Opacity Nodules by boundaries of GGO nodules to judge malignant or benign of lung tumors. However, radiologists need to look for the slices including the GGO nodule in CT volume data. It is time-consuming. This paper proposes a semi-supervised learning method based on the label propagation. First, a GGO nodule was labeled in one slice. Secondly, similarities were found by comparing with the labeled GGO nodule using the values of pixels. Finally, the GGO nodule of the other slices was labeled by iteration. Experimental results showed that the approach of this paper can find slices including the GGO nodule. The approach is better than the nearest neighbor algorithm in performance.
- リンク情報
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- DOI
- https://doi.org/10.1109/SNPD.2017.8022778
- DBLP
- https://dblp.uni-trier.de/rec/conf/snpd/YuanDDWMZ17
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000426449600090&DestApp=WOS_CPL
- URL
- http://dblp.uni-trier.de/db/conf/snpd/snpd2017.html#conf/snpd/YuanDDWMZ17
- Scopus
- https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85030861886&origin=inward
- Scopus Citedby
- https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85030861886&origin=inward
- ID情報
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- DOI : 10.1109/SNPD.2017.8022778
- ISBN : 9781509055043
- DBLP ID : conf/snpd/YuanDDWMZ17
- SCOPUS ID : 85030861886
- Web of Science ID : WOS:000426449600090