International audienceIn order to prevent bone fractures due to disease and ageing of the population, and to detect problems while still in their early stages, 3D bone micro architecture needs to be investigated and characterized. Here, we have developed various image processing and simulation techniques to investigate bone micro architecture and its mechanical stiffness. We have evaluated morphological, topological and mechanical bone features using artificial intelligence methods. A clinical study is carried out on two populations of arthritic and osteoporotic bone samples. The performances of Adaptive Neuro Fuzzy Inference System (ANFIS), Support Vector Machines (SVM) and Genetic Algorithm (GA) in classifying the different samples have been compared. Results show that the best separation success (100 %) is achieved with Genetic Algorithm

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The clinical process used to screen osteoporosis is the Bone Mineral Density (BMD). Since this density measurement does not cover the entire diagnosis range, work is being carried out on the segmentation of the bone and other complex porous media to provide quantitative information about their microarchitecture. Two shape classification techniques have been recently proposed in the literature. In this paper we compare these different methods and propose a new original rod/plate classification technique. The efficiency of the 3 processes is then studied on test vectors composed of both rods and plates, then applied on real trabecular bone samples. Results of this study emphasize the pros and cons of the 2 published techniques, and discuss the improvements of the new region-growth-based method. Finally, the interest of such a tool in osteoporosis screening is discussed.

Abstract-This work aims to estimate the apparent Young's modulus of real human trabecular bones using a numerical micro-macro approach. Cylindrical specimens of trabecular bone were extracted from human femur heads, cleaned and scanned using a SkyScan-1072 micro-computed tomography system. 3D volumetric tetrahedral grids were generated from the exploitation of the reconstructed images using original meshing techniques. Numerical compressive tests were simulated, assuming isotropic tissue Young's modulus for all elements. The large size of the volumes implies grids with a high number of nodes, which required the use of a large number of parallel processors in order to perform the finite element calculations. Numerical Young's moduli varied between 1300 MPa and 1600 MPa, with a good agreement with experiments.

Curve and surface thinning are widely-used skeletonization techniques for modeling objects in three dimensions. In the case of disordered porous media analysis, however, neither is really efficient since the internal geometry of the object is usually composed of both rod and plate shapes. This paper presents an alternative to compute a hybrid shape-dependent skeleton and its application to porous media. The resulting skeleton combines 2D surfaces and 1D curves to represent respectively the plate-shaped and rod-shaped parts of the object. For this purpose, a new technique based on neural networks is proposed: cascade combinations of complex wavelet transform (CWT) and complex-valued artificial neural network (CVANN). The ability of the skeleton to characterize hybrid shaped porous media is demonstrated on a trabecular bone sample. Results show that the proposed method achieves high accuracy rates about 99.78%-99.97%. Especially, CWT (2nd level)-CVANN structure converges to optimum results as high accuracy rate-minimum time consumption.

Compared to curve-based or surface-based skeletons, the hybrid skeleton better matches the geometry of the data. Each rod is represented by a one-voxel-thick arc and each plate is represented by a one-voxel-thick surface. The hybrid skeleton as well as the proposed classification algorithm introduce relevant parameters linked to the presence of plates in the trabecular bone data, showing that rods and plates contain independent information about trabeculae. The hybrid skeleton offers a new opportunity for precise studies of porous media such as trabecular bone.

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