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Automatic Segmentation of the Aortic Dissection Membrane from 3D CTA Images

Tamas Kovacs, Philippe Cattin, Hatem Alkadhi, Simon Wildermuth, and Gabor Székely
Medical Imaging and Augmented Reality (MIAR)
2006

Abstract

Acute aortic dissection is a life-threatening condition and must be diagnosed and treated promptly. For treatment planning the reliable identification of the true and false lumen is crucial. However, a fully automatic Computer Aided Diagnosis system capable of displaying the different lumens in an easily comprehensible and timely manner is still not available. In this paper we present a method that segments the entire aorta and then identifies the two lumens separated by the dissection membrane. The algorithm misdetected part of the membrane in only one of the 15 cases tested, where the aorta has not been significantly altered by the presence of aneurisms.


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@InProceedings{eth_biwi_00429,
  author = {Tamas Kovacs and Philippe Cattin and Hatem Alkadhi and Simon Wildermuth and and Gabor Székely},
  title = {Automatic Segmentation of the Aortic Dissection Membrane from 3D CTA Images},
  booktitle = {Medical Imaging and Augmented Reality (MIAR)},
  year = {2006},
  keywords = {}
}