3D automatic anatomy segmentation based on graph cut-oriented active appearance models

Xinjian Chen*, Jianhua Yao, Ying Zhuge, Ulas Bagci

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations


In this paper, we propose a novel 3D automatic anatomy segmentation method based on the synergistic combination of active appearance models (AAM), live wire (LW) and graph cut (GC). The proposed method consists of three main parts: model building, initialization and segmentation. For the model building part, an AAM model is constructed and the LW cost function is trained. For the initialization part, an improved iterative model refinement algorithm is proposed for the AAM optimization, which synergistically combines the AAM and LW method (OAAM). And a multi-object strategy is applied to help the object initialization. A pseudo 3D initialization strategy is employed to segment the organs slice by slice via multi-object OAAM method. The model constraints are applied to the initialization result. For the segmentation part, the object shape information generated from the initialization step is integrated into the GC cost computation. And an iterative GCOAAM method is proposed for object delineation. This method is a general method and can be applied to any organ segmentation. The proposed method was tested on the clinical liver and kidney CT data sets. The results showed the following: (a) an overall segmentation accuracy of true positive fraction>93.5%, and false positive fraction<0.2% can be achieved. (b) The initialization performance is improved by combining the AAM and LW. (c) The multi-object strategy greatly helps the initialization due to interobject constraints.

Original languageEnglish (US)
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Number of pages4
StatePublished - 2010
Externally publishedYes
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: Sep 26 2010Sep 29 2010

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880


Other2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/TerritoryHong Kong
CityHong Kong


  • Active appearance models
  • Graph cut
  • Live wire
  • Object segmentation

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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