A Deep Learning Pipeline to Automate High-Resolution Arterial Segmentation With or Without Intravenous Contrast.

Journal: Annals of surgery
Published Date:

Abstract

BACKGROUND: Existing methods to reconstruct vascular structures from a computerized tomography (CT) angiogram rely on contrast injection to enhance the radio-density within the vessel lumen. However, pathological changes in the vasculature may be present that prevent accurate reconstruction. In aortic aneurysmal disease, a thrombus adherent to the aortic wall within the expanding aneurysmal sac is present in >90% of cases. These deformations prevent the automatic extraction of vital clinical information by existing image reconstruction methods.

Authors

  • Anirudh Chandrashekar
    Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom.
  • Ashok Handa
    Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom.
  • Natesh Shivakumar
    Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom.
  • Pierfrancesco Lapolla
    Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom.
  • Raman Uberoi
    Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom.
  • Vicente Grau
    Department of Engineering Science, University of Oxford, Oxford, United Kingdom.
  • Regent Lee
    Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom.