Liver registration for the follow-up of hepatic tumors

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Abstract

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 [1], 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 4mm). © Springer-Verlag Berlin Heidelberg 2005.

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Charnoz, A., Agnus, V., Malandain, G., Forest, C., Tajine, M., & Soler, L. (2005). Liver registration for the follow-up of hepatic tumors. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3750 LNCS, pp. 155–162). https://doi.org/10.1007/11566489_20

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