TY - GEN
T1 - CT hepatic venography
T2 - 8th International Conference on Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005
AU - Fetita, Catalin
AU - Lucidarme, Olivier
AU - Prêteux, Françoise
AU - Grenier, Philippe
PY - 2005/12/1
Y1 - 2005/12/1
N2 - 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.
AB - 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.
U2 - 10.1007/11566489_102
DO - 10.1007/11566489_102
M3 - Conference contribution
C2 - 16686037
AN - SCOPUS:33744799177
SN - 3540293264
SN - 9783540293262
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 830
EP - 837
BT - Medical Image Computing and Computer-Assisted Intervention - MICCAI 2005 - 8th International Conference, Proceedings
Y2 - 26 October 2005 through 29 October 2005
ER -