Abstract
In this paper we present a novel statistical shape model for the liver based on a cubic Hermite mesh. With a small number of nodes (4, 12 or 20 for 1, 2 and 4 parametric cubic Hermite elements respectively) the complex liver shape can be captured with details. Such a model evolves from a generic ellipsoid-shaped template to fit to the data clouds of liver surfaces segmented from CT images. No landmarks on the data cloud are required to instruct the deformation of the parametric mesh. Through a Principle Component Analysis (PCA) for the nodal distribution on liver surfaces, a statistical shape model for the liver is generated. We found that 6 modes of the statistical model could interpret 96% of liver shape variations in 15 subject-specific livers. To evaluate the quality of node correspondence we devised a curvature criterion so that mis-alignments of nodes could be detected. In summary, a novel cubic Hermite mesh based statistical shape model is proposed. The mesh has a small set of nodes for PCA analysis, and the nodal correspondence across the shape database can be evaluated from a curvature criterion.
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We acknowledge the support of a Catalyst seed grant (Project number 3711560) from the Royal Society of New Zealand.
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Yu, H.B., Nakagawa, Y., Ho, H., Saito, A., Shimizu, A. (2018). Deformable Cubic Hermite Mesh Templates for Statistical Liver Shape Analysis. In: Reuter, M., Wachinger, C., Lombaert, H., Paniagua, B., Lüthi, M., Egger, B. (eds) Shape in Medical Imaging. ShapeMI 2018. Lecture Notes in Computer Science(), vol 11167. Springer, Cham. https://doi.org/10.1007/978-3-030-04747-4_9
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DOI: https://doi.org/10.1007/978-3-030-04747-4_9
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