Morphological Geodesic Active Contour Based Automatic Aorta Segmentation in Thoracic CT Images

  • Avijit Dasgupta
  • Sudipta Mukhopadhyay
  • Shrikant A. Mehre
  • Parthasarathi Bhattacharyya
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 460)

Abstract

Automatic aorta segmentation and quantification in thoracic computed tomography (CT) images is important for detection and prevention of aortic diseases. This paper proposes an automatic aorta segmentation algorithm in both contrast and non-contrast CT images of thorax. The proposed algorithm first detects the slice containing the carina region. Circular Hough Transform (CHT) is applied on the detected slice to localize ascending and descending aorta (circles with lowest variances) followed by a morphological geodesic active contour to segment the aorta from CT stack. The dice similarity coefficients (DSC) between the ground truth and the segmented output were found to be \(0.8845\pm 0.0584\) on LIDC-IDRI dataset.

Keywords

Cardiovascular diseases Computed tomography Aorta segmentation Computer-based automated segmentation Active contour 

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Copyright information

© Springer Science+Business Media Singapore 2017

Authors and Affiliations

  • Avijit Dasgupta
    • 1
  • Sudipta Mukhopadhyay
    • 1
  • Shrikant A. Mehre
    • 1
  • Parthasarathi Bhattacharyya
    • 2
  1. 1.Computer Vision and Image Processing Laboratory, Department of Electronics and Electrical Communication EngineeringIndian Institute of Technology KharagpurWest BengalIndia
  2. 2.Institute of Pulmocare & ResearchKolkataIndia

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