An Automated System for 3D Segmentation of CT Angiograms

  • Y. Wang
  • P. LiatsisEmail author
Part of the Augmented Vision and Reality book series (Augment Vis Real, volume 4)


This chapter presents a novel automated two-step algorithm for segmentation of the entire arterial tree in 3D contrast-enhanced Computed Tomography Angiography (CTA) datasets. In the first stage of the proposed algorithm, the main branches of the coronary arteries are extracted from the volume datasets based on a generalised active contour model by utilising both local and global intensity features. The use of local regional information allows for accommodating uneven brightness distribution across the image. The global energy term, derived from the histogram distribution of the input images, is used to deform the contour towards to desired boundaries without being trapped in local stationary points. Possible outliers, such as kissing vessel artefacts, are removed in the following stage by the proposed slice-by-slice correction algorithm. Experimental results on real clinical datasets have shown that our method is able to extract the major branches of the coronaries with an average distance of 0.7 voxels to the manually defined reference data. Furthermore, in the presence of kissing vessel artefacts, the outer surface of the coronary tree extracted by the proposed system is smooth and contains less erroneous segmentation as compared to the initial segmentation.


Computed tomography angiography 3D segmentation Coronary arteries Active contour models 

List of Abbreviations


Computed tomography angiography


Coronary artery disease


Computed tomography


Expectation maximisation


Gaussian mixture model


Left anterior descending


Left coronary artery


Left circumflex


Left main coronary


Right coronary artery


World Health Organization



The authors would like to acknowledge the support of City University, which enabled this research through the award of a University Research Studentship and Dr Gerry Carr-White and Rebecca Preston at St Thomas and Guys Hospitals for their invaluable advice and the provision of the CTA datasets.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.College of AstronauticsNanjing University of Aeronautics and AstronauticsNanjingChina
  2. 2.Department of Electrical and Electronic EngineeringCity University LondonLondonUnited Kingdom

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