A CMB Gibbs sampler for localized secondary anisotropies

As well as primary fluctuations, CMB temperature maps contain a wealth of additional information in the form of secondary anisotropies. Secondary effects that can be identified with individual objects, such as the thermal and kinetic Sunyaev-Zel'dovich (SZ) effects due to galaxy clusters, are difficult to unambiguously disentangle from foreground contamination and the primary CMB however. We develop a Bayesian formalism for rigorously characterising anisotropies that are localised on the sky, taking the TSZ and KSZ effects as an example. Using a Gibbs sampling scheme, we are able to efficiently sample from the joint posterior distribution for a multi-component model of the sky with many thousands of correlated physical parameters. The posterior can then be exactly marginalised to estimate properties of the secondary anisotropies, fully taking into account degeneracies with the other signals in the CMB map. We show that this method is computationally tractable using a simple implementation based on the existing Commander component separation code, and also discuss how other types of secondary anisotropy can be accommodated within our framework

High resolution bone material property assignment yields robust subject specific finite element models of complex thin bone structures

Accurate finite element (FE) modeling of complex skeletal anatomy requires high resolution in both meshing and the heterogeneous mapping of material properties onto the generated mesh. This study introduces Node-based elastic Modulus Assignment with Partial-volume correction (NMAP) as a new approach for FE material property assignment to thin bone structures. The NMAP approach incorporates point spread function based deblurring of CT images, partial-volume correction of CT image voxel intensities and anisotropic interpolation and mapping of CT intensity assignment to FE mesh nodes. The NMAP procedure combined with a derived craniomaxillo-facial skeleton (CMFS) specific density-isotropic elastic modulus relationship was applied to produce specimen-specific FE models of 6 cadaveric heads. The NMAP procedure successfully generated models of the complex thin bone structures with surface elastic moduli reflective of cortical bone material properties. The specimen-specific CMFS FE models were able to accurately predict experimental strains measured under in vitro temporalis and masseter muscle loading (r=0.93, slope=1.01, n=5). The strength of this correlation represents a robust validation for CMFS FE modeling that can be used to better understand load transfer in this complex musculoskeletal system. The developed methodology offers a systematic process-flow able to address the complexity of the CMFS that can be further applied to create high-fidelity models of any musculoskeletal anatomy

Restoration of Thickness, Density, and Volume for Highly Blurred Thin Cortical Bones in Clinical CT Images

In clinical CT images containing thin osseous structures, accurate definition of the geometry and density is limited by the scanner's resolution and radiation dose. This study presents and validates a practical methodology for restoring information about thin bone structure by volumetric deblurring of images. The methodology involves 2 steps: a phantom-free, post-reconstruction estimation of the 3D point spread function (PSF) from CT data sets, followed by iterative deconvolution using the PSF estimate. Performance of 5 iterative deconvolution algorithms, blind, Richardson-Lucy (standard, plus Total Variation versions), modified residual norm steepest descent (MRNSD), and Conjugate Gradient Least-Squares were evaluated using CT scans of synthetic cortical bone phantoms. The MRNSD algorithm resulted in the highest relative deblurring performance as assessed by a cortical bone thickness error (0.18 mm) and intensity error (150 HU), and was subsequently applied on a CT image of a cadaveric skull. Performance was compared against micro-CT images of the excised thin cortical bone samples from the skull (average thickness 1.08 ± 0.77 mm). Error in quantitative measurements made from the deblurred images was reduced 82% (p < 0.01) for cortical thickness and 55% (p < 0.01) for bone mineral mass. These results demonstrate a significant restoration of geometrical and radiological density information derived for thin osseous features

Structural biomechanics of the craniomaxillofacial skeleton under maximal masticatory loading: Inferences and critical analysis based on a validated computational model

The trend towards optimizing stabilization of the craniomaxillofacial skeleton (CMFS) with the minimum amount of fixation required to achieve union, and away from maximizing rigidity, requires a quantitative understanding of craniomaxillofacial biomechanics. This study uses computational modeling to quantify the structural biomechanics of the CMFS under maximal physiologic masticatory loading.Financial support for this work was provided by the Natural Sciences and Engineering Research Council of Canada (NSERC #RGPIN239206-11), and the Ontario Graduate Scholarship Program