Coronary lumen and plaque segmentation from CTA using higher-order shape prior

Yoshiro Kitamura, Yuanzhong Li, Wataru Ito, Hiroshi Ishikawa

研究成果: Conference contribution

15 被引用数 (Scopus)

抄録

We propose a novel segmentation method based on multi-label graph cuts utilizing higher-order potentials to impose shape priors. Each higher-order potential is defined with respect to a candidate shape, and takes a low value if and only if most of the voxels inside the shape are foreground and most of those outside are background. We apply this technique to coronary lumen and plaque segmentation in CT angiography, exploiting the prior knowledge that the vessel walls tend to be tubular, whereas calcified plaques are more likely globular. We use the Hessian analysis to detect the candidate shapes and introduce corresponding higher-order terms into the energy. Since each higher-order term has any effect only when its highly specific condition is met, we can add many of them at possible locations and sizes without severe side effects. We show the effectiveness of the method by testing it on the standardized evaluation framework presented at MICCAI segmentation challenge 2012. The method achieved values comparable to the best in each of the sensitivity and positive predictive value, placing it at the top in average rank.

本文言語English
ホスト出版物のタイトルMedical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - 17th International Conference, Proceedings
出版社Springer Verlag
ページ339-347
ページ数9
PART 1
ISBN(印刷版)9783319104034
DOI
出版ステータスPublished - 2014
イベント17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014 - Boston, MA, United States
継続期間: 2014 9 142014 9 18

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
番号PART 1
8673 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014
国/地域United States
CityBoston, MA
Period14/9/1414/9/18

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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