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Proceedings Paper

Detection of the aortic intimal tears by using 3D digital topology
Author(s): Christophe Lohou; Bruno Miguel
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Paper Abstract

Aortic dissection is a real problem of public health, it is a medical emergency and may quickly lead to death. Aortic dissection is caused by aortal tissue perforation because of blood pressure. It consists of tears (or holes of the intimal tissue) inside lumens. These tears are difficult to detect because they do not correspond to a filled organ to segment; they are usually visually retrieved by radiologists by examining gray level variation on successive image slices, but it remains a very difficult and error-prone task. Our purpose is to detect these intimal tears to help cardiac surgeons in making diagnosis. It would be useful either during a preoperative phase (visualization and location of tears, endoprothesis sizing); or during a peroperative phase (a registration of tears on angiographic images would lead to a more accuracy of surgeon's gestures and thus would enhance care of patient). At this aim, we use Aktouf et al.'s holes filling algorithm proposed in the field of digital topology. This algorithm permits the filling of holes of a 3D binary object by using topological notions - the holes are precisely the intimal tears for our aortic dissection images, after a first preprocessing step. As far as we know, this is the first time that such a proposal is made, even if it is a crucial data for cardiac surgeons. Our study is a preliminary and innovative work; our results are nevertheless considered satisfactory. This approach would also gain to be known to specialists of other diseases.

Paper Details

Date Published: 27 January 2011
PDF: 14 pages
Proc. SPIE 7864, Three-Dimensional Imaging, Interaction, and Measurement, 78640Z (27 January 2011); doi: 10.1117/12.877825
Show Author Affiliations
Christophe Lohou, Instituts Universitaires de Technologie (France)
Bruno Miguel, CHU Clermont-Ferrand (France)


Published in SPIE Proceedings Vol. 7864:
Three-Dimensional Imaging, Interaction, and Measurement
J. Angelo Beraldin; Ian E. McDowall; Atilla M. Baskurt; Margaret Dolinsky; Geraldine S. Cheok; Michael B. McCarthy; Ulrich Neuschaefer-Rube, Editor(s)

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