Liver registration for the follow-up of hepatic tumors.
In this paper we propose a new two step method to register the liver from two acquisitions. This registration helps experts to make an intra-patient follow-up for hepatic tumors. Firstly, an original and efficient tree matching is applied on different segmentations of the vascular system of a single patient. These vascular systems are segmented from CT-scan images acquired (every six months) during disease treatement, and then modeled as trees. Our method matches common bifurcations and vessels. Secondly, an estimation of liver deformation is computed from the results of the first step. This approach is validated on a large synthetic database containing cases with various deformation and segmentation problems. In each case, after the registration process, the liver recovery is very accurate (around 95%) and the mean localization error for 3D landmarks in liver is small (around 4 mm).
Charnoz
Arnaud
A
IRCAD R&D, Strasbourg, France.
Agnus
Vincent
V
Malandain
Grégoire
G
Forest
Clément
C
Tajine
Mohamed
M
Soler
Luc
L