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