Deep Learning to Automatically Segment and Analyze Abdominal Aortic Aneurysm from Computed Tomography Angiography.

Journal: Cardiovascular engineering and technology
PMID: 34997555

Abstract

PURPOSE: Although segmentation of Abdominal Aortic Aneurysms (AAA) thrombus is a crucial step for both the planning of endovascular treatment and the monitoring of the intervention's outcome, it is still performed manually implying time consuming operations as well as operator dependency. The present paper proposes a fully automatic pipeline to segment the intraluminal thrombus in AAA from contrast-enhanced Computed Tomography Angiography (CTA) images and to subsequently analyze AAA geometry.

Authors

  • Francesca Brutti
    Department of Mathematics, University of Trento, Trento, Italy.
  • Alice Fantazzini
    Department of Experimental Medicine, University of Genoa, Via Leon Battista Alberti, 2, 16132, Genoa, Italy. alice.fantazzini@edu.unige.it.
  • Alice Finotello
    Department of Integrated Surgical and Diagnostic Sciences, University of Genoa, Genoa, Italy.
  • Lucas Omar Müller
    Department of Mathematics, University of Trento, Trento, Italy.
  • Ferdinando Auricchio
    Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy.
  • Bianca Pane
    Vascular and Endovascular Surgery Unit, IRCCS Ospedale Policlinico San Martino, University of Genoa, Genoa, Italy.
  • Giovanni Spinella
    Vascular and Endovascular Surgery Unit, IRCCS Ospedale Policlinico San Martino, University of Genoa, Genoa, Italy.
  • Michele Conti
    Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy.

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