MISC

2019年

Segmentation of Bone Metastasis in CT Images Based on Modified HED

2019 19TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2019)
  • Yuchan Song
  • ,
  • Huimin Lu
  • ,
  • Hyoungseop Kim
  • ,
  • Seiichi Murakami
  • ,
  • Midori Ueno
  • ,
  • Takashi Terasawa
  • ,
  • Takatoshi Aoki

開始ページ
812
終了ページ
815
記述言語
英語
掲載種別
出版者・発行元
IEEE

Segmentation of the bone metastasis area in medical images can reduce the workload for diagnosis and treatment. However, there are various shapes and sizes of bone metastasis also affected by noise. As a result, it is difficult to segment using classical segmentation methods. In this paper, we propose a convolutional neural network model-based segmentation method. The proposed method easily predicts the contour and location of the lesion area using side connection and modified network. In this study, we modified again the modified HED network to match the characteristics of bone metastasis. The experimental results using the proposed method for segmenting bone metastasis in the lesion area has 79.8[%] of TP rate and 69.2[%] of IOU rate.

リンク情報
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000555707100116&DestApp=WOS_CPL
ID情報
  • ISSN : 2093-7121
  • Web of Science ID : WOS:000555707100116

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