Mesh-based vs. Image-based Statistical Appearance Model of the Human Femur: a Preliminary Comparison Study for the Creation of Finite Element Meshes

Bonaretti, Serena; Seiler, Christof; Boichon, Christelle; Büchler, Philippe; Reyes, Mauricio (2011). Mesh-based vs. Image-based Statistical Appearance Model of the Human Femur: a Preliminary Comparison Study for the Creation of Finite Element Meshes. In: Proceedings of the MICCAI Workshop on Mesh Processing in Medical Image Analysis. Westin Harbor Castle, Toronto, Canada. 18.09.2011.

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Statistical models have been recently introduced in computational orthopaedics to investigate the bone mechanical properties across several populations. A fundamental aspect for the construction of statistical models concerns the establishment of accurate anatomical correspondences among the objects of the training dataset. Various methods have been proposed to solve this problem such as mesh morphing or image registration algorithms. The objective of this study is to compare a mesh-based and an image-based statistical appearance model approaches for the creation of nite element(FE) meshes. A computer tomography (CT) dataset of 157 human left femurs was used for the comparison. For each approach, 30 finite element meshes were generated with the models. The quality of the obtained FE meshes was evaluated in terms of volume, size and shape of the elements. Results showed that the quality of the meshes obtained with the image-based approach was higher than the quality of the mesh-based approach. Future studies are required to evaluate the impact of this finding on the final mechanical simulations.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB

UniBE Contributor:

Bonaretti, Serena; Seiler, Christof; Büchler, Philippe and Reyes, Mauricio

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health

Language:

English

Submitter:

Factscience Import

Date Deposited:

04 Oct 2013 14:16

Last Modified:

05 Dec 2014 12:46

BORIS DOI:

10.7892/boris.4643

URI:

https://boris.unibe.ch/id/eprint/4643 (FactScience: 209188)

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