Extraction of fibre network architecture by X-ray tomography and prediction of elastic properties using an affine analytical model

This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Local structure of Mn in (La1-xHox) 2/3Ca1/3MnO3 studied by X-ray absorption fine structure

Results of X-ray absorption fine structure measurements in manganites (La1-xHox)2/3Ca1/3MnO3 with 0.15 < x < 0.50 are presented. When LaMnO3 is doped with a, divalent element such as Ca2+, substituting for La3+, holes are induced in the filled Mn d orbitais. This leads to a, strong ferromagnetic coupling between Mn sites. Ca ions in La1-xCa xMnO3 introduce a distortion of the crystal lattice and mixed valence Mn ions (Mn3+ and Mn4+). On the other hand, in manganites (La1-xHox)2/3Ca 1/3MnO3 the substitution of La for Ho causes a lattice distortion and induces a disorder, which reduces a magnetic interaction. The ferromagnetic transition temperature and conductivity decrease very quickly with increasing x. The magnetic and transport properties of compounds depend on the local atomic structure around Mn ions. The information on the bond lengths and Debye-Waller factor are obtained from the extended X-ray absorption fine structure (EXAFS) data analysis. The charge state of Mn is determined from the position of the absorption edge in X-ray absorption near edge structure (XANES) data. XAFS results are in good agreement with magnetic characteristics of the studied materials.

Cortical thickness estimation of the proximal femur from multi-view Dual-Energy X-ray Absorptiometry (DXA)

Hip fracture is the leading cause of acute orthopaedic hospital admission amongst the elderly, with around a third of patients not surviving one year post-fracture. Although various preventative therapies are available, patient selection is difficult. The current state-of-the-art risk assessment tool (FRAX) ignores focal structural defects, such as cortical bone thinning, a critical component in characterizing hip fragility. Cortical thickness can be measured using CT, but this is expensive and involves a significant radiation dose. Instead, Dual-Energy X-ray Absorptiometry (DXA) is currently the preferred imaging modality for assessing hip fracture risk and is used routinely in clinical practice. Our ambition is to develop a tool to measure cortical thickness using multi-view DXA instead of CT. In this initial study, we work with digitally reconstructed radiographs (DRRs) derived from CT data as a surrogate for DXA scans: this enables us to compare directly the thickness estimates with the gold standard CT results. Our approach involves a model-based femoral shape reconstruction followed by a data-driven algorithm to extract numerous cortical thickness point estimates. In a series of experiments on the shaft and trochanteric regions of 48 proximal femurs, we validated our algorithm and established its performance limits using 20 views in the range 0°-171°: estimation errors were 0:19 ± 0:53mm (mean +/- one standard deviation). In a more clinically viable protocol using four views in the range 0°-51°, where no other bony structures obstruct the projection of the femur, measurement errors were -0:07 ± 0:79 mm. © 2013 SPIE.