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Proceedings Paper

Fast 3D registration of multimodality tibial images with significant structural mismatch
Author(s): C. S. Rajapakse; M. J. Wald; J. Magland; X. H. Zhang; X. S. Liu; X. E. Guo; F. W. Wehrli
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Paper Abstract

Recently, micro-magnetic resonance imaging (μMRI) in conjunction with micro-finite element analysis has shown great potential in estimating mechanical properties - stiffness and elastic moduli - of bone in patients at risk of osteoporosis. Due to limited spatial resolution and signal-to-noise ratio achievable in vivo, the validity of estimated properties is often established by comparison to those derived from high-resolution micro-CT (μCT) images of cadaveric specimens. For accurate comparison of mechanical parameters derived from μMR and μCT images, analyzed 3D volumes have to be closely matched. The alignment of the micro structure (and the cortex) is often hampered by the fundamental differences of μMR and μCT images and variations in marrow content and cortical bone thickness. Here we present an intensity cross-correlation based registration algorithm coupled with segmentation for registering 3D tibial specimen images acquired by μMRI and μCT in the context of finite-element modeling to assess the bone's mechanical constants. The algorithm first generates three translational and three rotational parameters required to align segmented μMR and CT images from sub regions with high micro-structural similarities. These transformation parameters are then used to register the grayscale μMR and μCT images, which include both the cortex and trabecular bone. The intensity crosscorrelation maximization based registration algorithm described here is suitable for 3D rigid-body image registration applications where through-plane rotations are known to be relatively small. The close alignment of the resulting images is demonstrated quantitatively based on a voxel-overlap measure and qualitatively using visual inspection of the micro structure.

Paper Details

Date Published: 27 February 2009
PDF: 7 pages
Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 72620O (27 February 2009); doi: 10.1117/12.811753
Show Author Affiliations
C. S. Rajapakse, Univ. of Pennsylvania School of Medicine (United States)
M. J. Wald, Univ. of Pennsylvania School of Medicine (United States)
J. Magland, Univ. of Pennsylvania School of Medicine (United States)
X. H. Zhang, Columbia Univ. (United States)
X. S. Liu, Columbia Univ. (United States)
X. E. Guo, Columbia Univ. (United States)
F. W. Wehrli, Univ. of Pennsylvania School of Medicine (United States)


Published in SPIE Proceedings Vol. 7262:
Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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