Automatic estimation of the aortic lumen geometry by ellipse tracking

  • Pablo G. TahocesEmail author
  • Luis Alvarez
  • Esther González
  • Carmelo Cuenca
  • Agustín Trujillo
  • Daniel Santana-Cedrés
  • Julio Esclarín
  • Luis Gomez
  • Luis Mazorra
  • Miguel Alemán-Flores
  • José M. Carreira
Original Article



The shape and size of the aortic lumen can be associated with several aortic diseases. Automated computer segmentation can provide a mechanism for extracting the main features of the aorta that may be used as a diagnostic aid for physicians. This article presents a new fully automated algorithm to extract the aorta geometry for either normal (with and without contrast) or abnormal computed tomography (CT) cases.


The algorithm we propose is a fast incremental technique that computes the 3D geometry of the aortic lumen from an initial contour located inside it. Our approach is based on the optimization of the 3D orientation of the cross sections of the aorta. The method uses a robust ellipse estimation algorithm and an energy-based optimization technique to automatically track the centerline and the cross sections. The optimization involves the size and eccentricity of the ellipse which best fits the aorta contour on each cross-sectional plane. The method works directly on the original CT and does not require a prior segmentation of the aortic lumen. We present experimental results to show the accuracy of the method and its ability to cope with challenging CT cases where the aortic lumen may have low contrast, different kinds of pathologies, artifacts, and even significant angulations due to severe elongations.


The algorithm correctly tracked the aorta geometry in 380 of 385 CT cases. The mean of the dice similarity coefficient was 0.951 for aorta cross sections that were randomly selected from the whole database. The mean distance to a manually delineated segmentation of the aortic lumen was 0.9 mm for sixteen selected cases.


The results achieved after the evaluation demonstrate that the proposed algorithm is robust and accurate for the automatic extraction of the aorta geometry for both normal (with and without contrast) and abnormal CT volumes.


Aorta Ellipse tracking Centerline Cross section CT images 



This research has partially been supported by the MINECO projects references TIN2016-76373-P (AEI/FEDER, UE) and MTM2016-75339-P (AEI/FEDER, UE) (Ministerio de Economía y Competitividad, Spain).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. For this type of study, formal consent is not required.


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Copyright information

© CARS 2018

Authors and Affiliations

  1. 1.Department of Electronics and Computer ScienceUniversidad de Santiago de CompostelaSantiago de CompostelaSpain
  2. 2.CTIMUniversidad de Las Palmas de Gran CanariaLas Palmas de Gran CanariaSpain
  3. 3.Complejo Hospitalario Universitario de Santiago (CHUS)Santiago de CompostelaSpain

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