Automated method for extraction of lung tumors using a machine learning classifier with knowledge of radiation oncologists on data sets of planning CT and FDG-PET/CT images

Hidetaka Arimura, Ze Jin, Yoshiyuki Shioyama, Katsumasa Nakamura, Taiki Magome, Masayuki Sasaki

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

5 被引用数 (Scopus)

抄録

We have developed an automated method for extraction of lung tumors using a machine learning classifier with knowledge of radiation oncologists on data sets of treatment planning computed tomography (CT) and 18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET)/CT images. First, the PET images were registered with the treatment planning CT images through the diagnostic CT images of PET/CT. Second, six voxel-based features including voxel values and magnitudes of image gradient vectors were derived from each voxel in the planning CT and PET /CT image data sets. Finally, lung tumors were extracted by using a support vector machine (SVM), which learned 6 voxel-based features inside and outside each true tumor region determined by radiation oncologists. The results showed that the average DSCs for 3 and 6 features for three cases were 0.744 and 0.899, and thus the SVM may need 6 features to learn the distinguishable characteristics. The proposed method may be useful for assisting treatment planners in delineation of the tumor region.

本文言語英語
ホスト出版物のタイトル2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
ページ2988-2991
ページ数4
DOI
出版ステータス出版済み - 10 31 2013
イベント2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, 日本
継続期間: 7 3 20137 7 2013

出版物シリーズ

名前Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN(印刷版)1557-170X

その他

その他2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
国/地域日本
CityOsaka
Period7/3/137/7/13

All Science Journal Classification (ASJC) codes

  • 信号処理
  • 生体医工学
  • コンピュータ ビジョンおよびパターン認識
  • 健康情報学

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