Automated 3D vascular segmentation in CT hepatic venography

Catalin Fetita; Olivier Lucidarme; Francoise Preteux

doi:10.1117/12.620880

30 August 2005 Automated 3D vascular segmentation in CT hepatic venography

Catalin Fetita, Olivier Lucidarme, Francoise Preteux

Proceedings Volume 5916, Mathematical Methods in Pattern and Image Analysis; 59160B (2005) https://doi.org/10.1117/12.620880
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

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.

Citation Download Citation

Catalin Fetita, Olivier Lucidarme, and Francoise Preteux "Automated 3D vascular segmentation in CT hepatic venography", Proc. SPIE 5916, Mathematical Methods in Pattern and Image Analysis, 59160B (30 August 2005); https://doi.org/10.1117/12.620880

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