Accurate liver extraction using a local-thickness-based graph-cut approach

Yasuhiro Kobayashi, Masanori Hariyama, Mitsugi Shimoda, Keiichi Kubota

研究成果: Conference contribution

抄録

This article presents an accurate and automatic approach to extract a liver from CT images for oncologic surgery planning. Our algorithm exploits graph cut segmentation, which perform global optimization. The quality of graph cut segmentation strongly depends on the edge image that gives prior knowledge about locations of foreground and background regions. In order to get a good edge image, a liver candidate region is extracted based on three types of liver structure models: intensity model, shape model, and blood vessel model. Moreover, the "local-thickness" image of the liver candidate region is used as the edge image. The experimental results show that the use of local-thickness edge image can avoid the over-extraction of anatomical structures surrounding the liver.

本文言語English
ホスト出版物のタイトルProceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015
編集者Hamid R. Arabnia, Leonidas Deligiannidis, Fernando G. Tinetti, George Jandieri, Gerald Schaefer, Ashu M. G. Solo
出版社CSREA Press
ページ315-318
ページ数4
ISBN(電子版)1601324049, 9781601324047
出版ステータスPublished - 2015
イベント2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015, at WORLDCOMP 2015 - Las Vegas, United States
継続期間: 2015 7 272015 7 30

出版物シリーズ

名前Proceedings of the 2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015

Conference

Conference2015 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2015, at WORLDCOMP 2015
国/地域United States
CityLas Vegas
Period15/7/2715/7/30

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ グラフィックスおよびコンピュータ支援設計

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