Medical image segmentation by combining graph cuts and oriented active appearance models

Xinjian Chen*, Jayaram K. Udupa, Ulas Bagci, Ying Zhuge, Jianhua Yao

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

176 Scopus citations

Abstract

In this paper, we propose a novel method based on a strategic combination of the active appearance model (AAM), live wire (LW), and graph cuts (GCs) for abdominal 3-D organ segmentation. The proposed method consists of three main parts: model building, object recognition, and delineation. In the model building part, we construct the AAM and train the LW cost function and GC parameters. In the recognition part, a novel algorithm is proposed for improving the conventional AAM matching method, which effectively combines the AAM and LW methods, resulting in the oriented AAM (OAAM). A multiobject strategy is utilized to help in object initialization. We employ a pseudo-3-D initialization strategy and segment the organs slice by slice via a multiobject OAAM method. For the object delineation part, a 3-D shape-constrained GC method is proposed. The object shape generated from the initialization step is integrated into the GC cost computation, and an iterative GC-OAAM method is used for object delineation. The proposed method was tested in segmenting the liver, kidneys, and spleen on a clinical CT data set and also on the MICCAI 2007 Grand Challenge liver data set. The results show the following: 1) The overall segmentation accuracy of true positive volume fraction TPVF > 94.3% and false positive volume fraction FPVF < 0.2% can be achieved; 2) the initialization performance can be improved by combining the AAM and LW; 3) the multiobject strategy greatly facilitates initialization; 4) compared with the traditional 3-D AAM method, the pseudo-3-D OAAM method achieves comparable performance while running 12 times faster; and 5) the performance of the proposed method is comparable to state-of-the-art liver segmentation algorithm. The executable version of the 3-D shape-constrained GC method with a user interface can be downloaded from http://xinjianchen.wordpress.com/research/.

Original languageEnglish (US)
Article number6144010
Pages (from-to)2035-2046
Number of pages12
JournalIEEE Transactions on Image Processing
Volume21
Issue number4
DOIs
StatePublished - Apr 2012
Externally publishedYes

Keywords

  • Active appearance model (AAM)
  • graph cut (GC)
  • live wire (LW)
  • object segmentation

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design

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