@inproceedings{fae861ccd8d44c8abf4b20aadd37c874,
title = "A Semi-automated image segmentation approach for computational fluid dynamics studies of aortic dissection",
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.",
author = "Anderson, {Jeff R.} and Christof Karmonik and Yannick Georg and Jean Bismuth and Lumsden, {Alan B.} and Adeline Schwein and Mickael Ohana and Fabien Thaveau and Nabil Chakfe",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014 ; Conference date: 26-08-2014 Through 30-08-2014",
year = "2014",
month = nov,
day = "2",
doi = "10.1109/EMBC.2014.6944680",
language = "English (US)",
series = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4727--4730",
booktitle = "2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014",
address = "United States",
}