Automated Segmentation of 3D CT Images Based on Statistical Atlas and Graph Cuts

  • Akinobu Shimizu
  • Keita Nakagomi
  • Takuya Narihira
  • Hidefumi Kobatake
  • Shigeru Nawano
  • Kenji Shinozaki
  • Koich Ishizu
  • Kaori Togashi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6533)

Abstract

This paper presents an effective combination of a statistical atlas-based approach and a graph cuts algorithm for fully automated robust and accurate segmentation. Major contribution of this paper is proposal of two new submodular energies for graph cuts. One is shape constrained energy derived from a statistical atlas based segmentation and the other is for constraint from a neighbouring structure. The effectiveness of the proposed energies was demonstrated using a synthesis image with different errors in shape estimation and clinical CT volumes of liver and lung.

Keywords

segmentation CT shape prior neighbour constraint graph cuts statistical atlas 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Akinobu Shimizu
    • 1
  • Keita Nakagomi
    • 1
  • Takuya Narihira
    • 1
  • Hidefumi Kobatake
    • 1
  • Shigeru Nawano
    • 2
  • Kenji Shinozaki
    • 3
  • Koich Ishizu
    • 4
  • Kaori Togashi
    • 4
  1. 1.Tokyo University of Agriculture and TechnologyTokyoJapan
  2. 2.International University of Health and WelfareTokyoJapan
  3. 3.National Kyusyu Cancer CenterFukuokaJapan
  4. 4.Kyoto UniversityKyotoJapan

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