Dr. Jeremy F. Magland Profile

Dr. Jeremy F. Magland

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Proceedings Article | 28 February 2009 Paper

Fast 3D registration of multimodality tibial images with significant structural mismatch

C. Rajapakse, M. Wald, J. Magland, X. Zhang, X. Liu, X. Guo, F. Wehrli

Proceedings Volume 7262, 72620O (2009) https://doi.org/10.1117/12.811753

KEYWORDS: Bone, Image registration, 3D image processing, Image segmentation, Image resolution, Signal to noise ratio, In vivo imaging, Spatial resolution, 3D modeling, Image processing algorithms and systems

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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.

Proceedings Article | 12 March 2008 Paper

Improved 3D skeletonization of trabecular bone images derived from in vivo MRI

Jeremy Magland, Felix Wehrli

Proceedings Volume 6916, 691618 (2008) https://doi.org/10.1117/12.771002

KEYWORDS: Bone, 3D image processing, Magnetic resonance imaging, In vivo imaging, Image processing, Binary data, 3D metrology, Signal to noise ratio, 3D modeling, Data acquisition

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Independent of overall bone density, 3D trabecular bone (TB) architecture has been shown to play an important role in conferring strength to the skeleton. Advances in imaging technologies such as micro-computed tomography (CT) and micro-magnetic resonance (MR) now permit in vivo imaging of the 3D trabecular network in the distal extremities. However, various experimental factors preclude a straightforward analysis of the 3D trabecular structure on the basis of these in vivo images. For MRI, these factors include blurring due to patient motion, partial volume effects, and measurement noise. While a variety of techniques have been developed to deal with the problem of patient motion, the second and third issues are inherent limitations of the modality. To address these issues, we have developed a series of robust processing steps to be applied to a 3D MR image and leading to a 3D skeleton that accurately represents the trabecular bone structure. Here we describe the algorithm, provide illustrations of its use with both specimen and in vivo micro-MR images, and discuss the accuracy and quantify the relationship between the original bone structure and the resulting 3D skeleton volume.

Proceedings Article | 11 March 2008 Paper

Efficient 3D rigid-body registration of micro-MR and micro-CT trabecular bone images

C. Rajapakse, J. Magland, S. Wehrli, X. Zhang, X. Liu, X. Guo, F. Wehrli

Proceedings Volume 6914, 69142Z (2008) https://doi.org/10.1117/12.770931

KEYWORDS: Image registration, 3D image processing, Bone, Image segmentation, Image resolution, In vivo imaging, Tomography, 3D modeling, Magnetism, Matrices

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Registration of 3D images acquired from different imaging modalities such as micro-magnetic resonance imaging (µMRI) and micro-computed tomography (µCT) are of interest in a number of medical imaging applications. Most general-purpose multimodality registration algorithms tend to be computationally intensive and do not take advantage of the shape of the imaging volume. Multimodality trabecular bone (TB) images of cylindrical cores, for example, tend to be misaligned along and around the axial direction more than that around other directions. Additionally, TB images acquired by µMRI can differ substantially from those acquired by µCT due to apparent trabecular thickening from magnetic susceptibility boundary effects and non-linear intensity correspondence. However, they share very similar contrast characteristics since the images essentially represent a binary tomographic system. The directional misalignment and the fundamental similarities of the two types of images can be exploited to achieve fast 3D registration. Here we present an intensity cross-correlation based 3D registration algorithm for registering 3D specimen images from cylindrical cores of cadaveric TB acquired by µMRI and µCT in the context of finite-element modeling to assess the bone's mechanical constants. The algorithm achieves the desired registration by first coarsely approximating the three translational and three rotational parameters required to align the µMR images to the µCT scan coordinate frame and fine-tuning the parameters in the neighborhood of the approximate solution. The algorithm described here is suitable for 3D rigid-body image registration applications where through-plane rotations are known to be relatively small. The accuracy of the technique is constrained by the image resolution and in-plane angular increments used.

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