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Proceedings Paper

Automated 3D vascular segmentation in CT hepatic venography
Author(s): Catalin Fetita; Olivier Lucidarme; Francoise Preteux
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Paper Abstract

In the framework of preoperative evaluation of the hepatic venous anatomy in living-donor liver transplantation or oncologic rejections, this paper proposes an automated approach for the 3D segmentation of the liver vascular structure from 3D CT hepatic venography data. The developed segmentation approach takes into account the specificities of anatomical structures in terms of spatial location, connectivity and morphometric properties. It implements basic and advanced morphological operators (closing, geodesic dilation, gray-level reconstruction, sup-constrained connection cost) in mono- and multi-resolution filtering schemes in order to achieve an automated 3D reconstruction of the opacified hepatic vessels. A thorough investigation of the venous anatomy including morphometric parameter estimation is then possible via computer-vision 3D rendering, interaction and navigation capabilities.

Paper Details

Date Published: 30 August 2005
PDF: 12 pages
Proc. SPIE 5916, Mathematical Methods in Pattern and Image Analysis, 59160B (30 August 2005); doi: 10.1117/12.620880
Show Author Affiliations
Catalin Fetita, INT/ARTEMIS (France)
Olivier Lucidarme, Pitie-Salpetriere Hospital (France)
Francoise Preteux, INT/ARTEMIS (France)

Published in SPIE Proceedings Vol. 5916:
Mathematical Methods in Pattern and Image Analysis
Jaakko T. Astola; Ioan Tabus; Junior Barrera, Editor(s)

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