Abstract
Preventing complications during hepatic surgery in living-donor transplantation or in oncologic resections requires a careful preoperative analysis of the hepatic venous anatomy. Such an analysis relies on CT hepatic venography data, which enhances the vascular structure due to contrast medium injection. However, a 3D investigation of the enhanced vascular anatomy based on typical computer vision tools is ineffective because of the large amount of occlusive opacities to be removed. This paper proposes an automated 3D approach for the segmentation of the vascular structure in CT hepatic venography, providing the appropriate tools for such an investigation. The developed methodology relies on advanced topological and morphological operators applied in mono-and multiresolution filtering schemes. It allows to discriminate the opacified vessels from the bone structures and liver parenchyma regardless of noise presence or inter-patient variability in contrast medium dispersion. The proposed approach was demonstrated at different phases of hepatic perfusion and is currently under extensive validation in clinical routine. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Fetita, C., Lucidarme, O., Prêteux, F., & Grenier, P. (2005). CT hepatic venography: 3D vascular segmentation for preoperative evaluation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3750 LNCS, pp. 830–837). https://doi.org/10.1007/11566489_102
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