Patient-specific meshless model for whole-body image registration

Mao Li, Karol Miller, Grand Joldes, R.M.D. Kikinìs, Adam Wittek

Research output: Chapter in Book/Conference paperConference paperpeer-review

5 Citations (Scopus)


© Springer International Publishing Switzerland 2014. Non-rigid registration algorithms that align source and target images play an important role in image-guided surgery and diagnosis. For problems involving large differences between images, such as registration of whole-body radiographic images, biomechanical models have been proposed in recent years. Biomechanical registration has been dominated by Finite Element Method (FEM). In practice, major drawback of FEM is a long time required to generate patient-specific finite element meshes and divide (segment) the image into nonoverlapping constituents with different material properties. We eliminate timeconsuming mesh generation through application of Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithm that utilises a computational grid in a form of cloud of points. To eliminate the need for segmentation, we use fuzzy tissue classification algorithm to assign the material properties to meshless grid. Comparison of the organ contours in the registered (i.e. source image warped using deformations predicted by our patient-specific meshless model) and target images indicate that our meshless approach facilitates accurate registration of whole-body images with local misalignments of up to only two voxels.
Original languageEnglish
Title of host publicationBiomedical Simulation
Place of PublicationStrasbourg
ISBN (Print)9783319120560
Publication statusPublished - 2014
Event6th International Symposium on Biomedical Simulation - Strasbourg, France
Duration: 16 Oct 201417 Oct 2014


Conference6th International Symposium on Biomedical Simulation


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