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

  • Cognitive Computing and Medical Imaging

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

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.

Original languageEnglish
Title of host publicationMedical Imaging 2014
Subtitle of host publicationImage Processing
PublisherSPIE
ISBN (Print)9780819498274
DOIs
StatePublished - 2014
Externally publishedYes
EventMedical Imaging 2014: Image Processing - San Diego, CA, United States
Duration: 16 Feb 201418 Feb 2014

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume9034
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2014: Image Processing
Country/TerritoryUnited States
CitySan Diego, CA
Period16/02/1418/02/14

Keywords

  • Finite element methods
  • Graph matching
  • Liver
  • Physical
  • Registration

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