A semi-automated image segmentation approach for computational fluid dynamics studies of aortic dissection. Academic Article uri icon

Overview

abstract

  • Computational studies of aortic hemodynamics require accurate and reproducible segmentation of the aortic tree from whole body, contrast enhanced CT images. Three methods were vetted for segmentation. A semi-automated approach that utilizes denoising, the extended maxima transform, and a minimal amount of manual segmentation was adopted.

publication date

  • January 1, 2014

Research

keywords

  • Aorta
  • Hydrodynamics
  • Image Processing, Computer-Assisted

Identity

Scopus Document Identifier

  • 84929493287

Digital Object Identifier (DOI)

  • 10.1109/EMBC.2014.6944680

PubMed ID

  • 25571048

Additional Document Info

volume

  • 2014