Two-step FEM-based Liver-CT registration: improving internal and external accuracy

Cristina Oyarzun Laura; Klaus Drechsler; Stefan Wesarg

doi:10.1117/12.2043592

21 March 2014 Two-step FEM-based Liver-CT registration: improving internal and external accuracy

Cristina Oyarzun Laura, Klaus Drechsler, Stefan Wesarg

Proceedings Volume 9034, Medical Imaging 2014: Image Processing; 90343K (2014) https://doi.org/10.1117/12.2043592
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

To know the exact location of the internal structures of the organs, especially the vasculature, is of great importance for the clinicians. This information allows them to know which structures/vessels will be affected by certain therapy and therefore to better treat the patients. However the use of internal structures for registration is often disregarded especially in physical based registration methods. In this paper we propose an algorithm that uses finite element methods to carry out a registration of liver volumes that will not only have accuracy in the boundaries of the organ but also in the interior. Therefore a graph matching algorithm is used to find correspondences between the vessel trees of the two livers to be registered. In addition to this an adaptive volumetric mesh is generated that contains nodes in the locations in which correspondences were found. The displacements derived from those correspondences are the input for the initial deformation of the model. The first deformation brings the internal structures to their final deformed positions and the surfaces close to it. Finally, thin plate splines are used to refine the solution at the boundaries of the organ achieving an improvement in the accuracy of 71%. The algorithm has been evaluated in CT clinical images of the abdomen.

Citation Download Citation

Cristina Oyarzun Laura, Klaus Drechsler, and Stefan Wesarg "Two-step FEM-based Liver-CT registration: improving internal and external accuracy", Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 90343K (21 March 2014); https://doi.org/10.1117/12.2043592

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