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Porous metals are found to be suitable as orthopedic scaffolds. However, only limited control over the internal architecture can be achieved using conventional design methods. The architecture with porosity variation strategy mimicking natural bone is critical to gain favorable combination of mechanical and biological properties for orthopedic implants. In this regard, a topology optimization method with customized morphology and mechanical properties derived from the trabecular bone was proposed to design three-dimensional architectures with gradient porosity resembling the porous structure of bone. In particular, the elastic constants for the trabecular bone were better predicted when the bone volume fraction was supplemented with a three-dimensional structural parameter, i.e., degree of anisotropy. These constants were set as the optimization constrains for morphology control. Then the porous titanium structures were manufactured by selective laser melting technology (SLM). The physical characteristics, mechanical properties of the scaffolds were compared systematically. The experimental results revealed that the as-built samples with the proposed method lead to a good match of morphological accuracy and mechanical properties to that of the bone. It demonstrates that the proposed topology optimization method with controlled morphology and mechanical properties provides an efficient manner for the biomimetic design of orthopedic implants.

Today, the technological explosion has led to the digitalization of many already proven applications thanks to the promising results it has provided. In fact, Computer-Aided Diagnosis (CAD) is one of the applications where digitization has played an effective role, especially with the advancement of medical imaging technology. Osteoporosis is one of the diseases diagnosed by computer today. It is a major skeletal disorder that predominantly affects women and has become a major impact on public health. this is a condition characterized by gradually decreased bone mass and deteriorated bone structure, causing bone fragility and fracture risk, especially of the wrist, hip, and spine. Considering the importance of machine learning in CAD systems design. This article provides an overview of various machine learning models for predicting osteoporosis risk. We will review the latest research in the AI application to predict osteoporosis and in particular that related to deep learning used to model the risk of fragility fracture and to help identify and segment images.

In this work, the feasibility of photoacoustic time-frequency spectral analysis (PA- TFSA) for bone microstructure evaluation was investigated. In order to get the main frequency component at each moment, the parameter “power-weighted mean frequency (PWMF)” was used to quantify the frequency spectrum of bone PA signals at each moment. The simulations on bone samples with different mean trabecular thickness (MTT) and ex vivo experiments on rabbit distal femoral metaphysis before and after treatment using ethylenediaminetetraacetic acid (EDTA) solution were conducted. Both the results show that there are higher frequency components in the photoacoustic time frequency spectrum (PA- TFS) as the MTT decreases. The photoacoustic parameters, the maximal PWMF and the averaged PWMF within 1 µs are related to the size characteristics of the trabecular bone, and show significant statistical differences (p

In this work, we introduce an atlas-based segmentation method for lower leg tissues at 4%, 38%, and 66% tibial length. Our goal is to model the shape of the lower leg tissue types and to identify hard and soft tissues in an automated way. In our methodology, we implemented B-spline based free form deformation (FFD), and symmetric diffeomorphic demons (SDD) deformable models for nonlinear registration, and compared their performances for atlas-based segmentation accuracy on our pQCT data. Overall, we concluded that atlas-based segmentation is a promising technique, especially in the presence of noise and other types of image degradation. We also observed that the diffeomorphic demons algorithm may produce more accurate deformation fields than FFD. On the other hand, FFD produced smoother deformations than SDD. Quantitative analysis using the Dice similarity coefficient (DSC), showed that FFD was slightly better than SDD in identification of the trabecular bone tissue in 4% tibia. At 38% tibial length, SDD produced consistently higher DSC values than FFD, while at 66% tibia, FFD produced slightly higher segmentation accuracy.

Osteoporosis is a disease characterized by the gradual deterioration of a trabecular bone, changing its density and composition. Dielectric constant of the trabecular bone, which is affected by the bone composition, changes propagation characteristics of electromagnetic (EM) waves within this medium. The goal of this work is to study the dependence of the characteristics of the EM wave propagation on the osteoporosis severity degree. A human finger is considered as the object of the study. This paper presents results of modeling the finger EM properties and propagation of the EM wave through the finger for various osteoporosis severity degree levels. Results of extensive experimental studies with EM wave propagation through the human fingers have been performed and are presented in the paper. Two different approaches to the problem of EM injection into the finger were considered: the coaxial probe method and Fabry-Perot resonator formed by the finger placed between a planar antenna and a reflecting surface. The results of the wave propagation analysis within the fingers containing healthy and diseased bones are used for estimation of the osteoporosis severity degree. A numerical criterion intended for an estimation of the osteoporosis severity degree is suggested.

The most beautiful recognizable feature of the toco toucan is its large and colorful bill. Despite its importance, such as in feeding and acting as a thermal regulator, few systematic approaches have been proposed for characterizing its structural organization. A framework for identifying and characterizing the trabecular bone tissue located inside the bill is reported in this work. An image processing pipeline for segmenting the trabecular bones is proposed, followed by the derivation of a 3D coordinate system defined by the shape of the bill. These coordinates are then used for further characterization of the mass distribution inside the bill.

Osteoporosis is a systemic skeletal disease, which is characterized by the deterioration of microstructures and the decrease of bone mineral density (BMD). Ultrasonic backscatter technique has a promising potential to evaluate microstructures and BMD of cancellous bone for the diagnosis of osteoporosis. The dynamic time warping (DTW)algorithm, measuring the similarity between two signals, has been widely used in speech and image recognition. The purpose of this study is to investigate the feasibility of the DTW algorithm in extracting features from ultrasonic backscatter signals and estimating the microstructure of cancellous bones. Ultrasonic backscatter measurements were performed on twenty-six bovine cancellous bone specimens using an ultrasonic backscatter bone diagnostic system with a focused broadband transducer, which has a center frequency of 1.04 MHz. The dynamic time warped distance (DTWD)feature was extracted from the cost matrix between the ultrasonic backscatter signals and the reference signal. The associations between ultrasonic backscatter features (including DTWD)and trabecular microstructures (i.e., the average trabecular number (Tb. N)and the average trabecular bone spacing (Tb. Sp)), and BMD were analyzed using the simple Pearson's correlations and Partial correlations. The results showed that the DTWD significantly correlated with the Tb.N (R = −0.86±0.09, p

A biological object is considered as a complicated dielectric structure with losses. Particularly, the dielectric properties of human bones depend on their state (normal or diseased). Osteoporosis is characterized by a trabecular bone structure deterioration changing the bone density and dielectric permittivity. We modeled the electromagnetic (EM) wave propagation trough the human wrist considered as a multilayer structure comprising bone, muscle, fat etc. EM properties of the wrist bone affect the propagating EM wave. The aim of this study is to investigate the dependence of wave propagation characteristics on the osteoporosis severity, expressed as a change of dielectric permittivity of the wrist bone, which may be useful for osteoporosis diagnostic. Results of the full wave wrist model simulations with different degrees of the osteoporosis severity are presented and discussed.

This paper proposes a method for diagnosis of osteoporosis disease by analyzing the trabecular bone pattern. The idea behind such a technique is to assist the physician to detect, control and treat various forms of osteoporosis in the early stage. The degree of disease is calculated by analyzing trabecular bone pattern using series of image processing techniques and common image quality measures. The experimental results conducted on twenty people reveals that proposed method identifies the disease by specifying the intensity of the disease.

A panoramic radiography image provides not only details of teeth but also rich information about trabecular bone. Recent studies have addressed the correlation between trabecular bone structure and osteoporosis. In this paper, we collect a dataset containing 40 images from 40 different subjects, and construct a new methodology based on a two-stage classification framework that combines multiple trabecular bone regions of interest (ROIs) for osteoporosis prescreening. In the first stage, different support vector machines (SVMs) are adopted to describe different information of different ROIs. In the second stage, the output probabilities of the first stage are effectively combined by using an additional linear SVM model to make a final prediction. Based on our two stage model, we test the performance of different image features by using leave-one-out cross-valuation and analysis of variance rules. The results suggest that the proposed method with the HOG (histogram of oriented gradients) feature achieves the best overall accuracy.

The segmentation of the bone in HR-pQCT (High Resolution peripheral Quantitative Computed Tomography) images remains a challenging task due to the image characteristics and the complex structure of the bone (cortical and trabecular). In this paper, we address the problem of separating the cortical bone from the background and the trabecular bone. We propose a novel approach to segment the cortical bone using dual active contours. This new concept allows the two contours to interact with each other and evolve to delineate the cortical bone. The energy of the two contours is based on the local information along the curve to be able to handle the intensity inhomogeneity, the noise characteristics and the motion artefacts in such images. Unlike state of art methods, the proposed technique can segment accurately the cortical bone in the different sites (proximal and ultra-distal). Finally, to test the robustness and accuracy of our proposed method, we compared the computed segmentation results of each method to the ground truth. Our proposed approach gives a higher Dice similarity coefficient in both proximal and ultra-distal sites.

Osteoporosis is a disease characterized by low bone mass and deterioration of micro-architectural bone tissue, which provokes an increased risk of fracture. This work treats the texture characterization of trabecular bone radiographs. The goal is to analyse according to clinical research a group of 174 subjects: 87 osteoporotic patients with various bone fracture types and 87 healthy subjects. In order to characterize osteoporosis, a method of lacunarity measurement for grayscale image is used. This approach allowed the discrimination between healthy subjects and patients with osteoporosis. The results show an improved classification rate compared to another work [1].

We assessed the regional variations in density and shear strength within the human thoracic vertebral body using donated cadaveric tissues. Shear strength was significantly lower in the anterior than in the lateral region. From the inferior to the superior endplates, shear strength and maximum load to failure decreased by 23% and 33%, respectively. Trabecular bone maximum load carrying capacity was 5 times higher in the lateral and 4.5 times higher in the central than in the anterior regions. Mechanical strength positively correlated with ash density and most closely with material density.

In this poster we apply the 3D-cubeness shape descriptor from [1] (C(S)) to a sample (n=37, vertebra, male) of cubic trabecular bone volumes obtained by microcomputerized tomography (CT). Also theoretical models with a decreasing number of assigned trabecular voxels, irrespective their position, were analyzed. Our results show that C(S) correctly classifies the theoretical and the trabecular bone volumes according to their bone volume density (BV/TV) parameter (r=0.97; r2=0.95), and trabecular fractal dimension (FD-BV) (r=0.87; r2=0.80). This provides an alternative to standard global 3D-morphometrical methods used for assessing the microarchitectural deterioration of trabecular bone.

Working with bone mimicking phantoms is necessary for the development of ultrasonic methods for bone characterization. The phantoms currently available for trabecular bone do not mimic some of the bone ultrasonic properties accurately. We report the fabrication of anisotropic phantoms, constituted of square rods, using a modified stereolithographic printer. Ultrasound pulse propagation was performed in the phantoms and the fast and slow waves could be observed for a propagation along the main orientation of the rods. This work demonstrates the feasibility of printing anisotropic structures with a typical size comparable to the size of bone trabeculae. Further work will be directed towards high resolution printing of full trabecular micro-structures.

Reliable quantification of mechanical constants of bone tissue is an open issue with relevance for the diagnostic of bone quality disorders, such as osteoporosis. Two open questions are addressed here: the suitability of Biot's poroelasticity to explain the complex propagation patterns of ultrasound through trabecular bone, combined with a two-parameter homogeneization model, and to determine the confidence intervals of the reconstruction. An information-theory based probabilistic inversion framework is proposed for the first time to answer both questions. This work is aimed at (i) reconstructing the Biot-theory parameters that simulate the ultrasonic transmission through a set of trabecular bone samples, as well as their plausible ranges, (ii) evaluate which parameters are reconstructable and which not, as well as the degree of plausibility of Biot's theory to explain the experimental measurements, (iii) merge information provided by a two-parameter constitutive model to add knowledge to the reconstruction process, and evaluate the plausibility of this new hypothesis, again through the information-theory framework, and (iv) validate the reconstruction against independent tests.

Trabecular bone consists of a network of tiny strands and plates. Micro-structural features of trabecular bone include thickness, relative volume, spacing and connectivity. The accurate evaluation of these features is of significant interest in the assessment of the mechanical and transport properties of bone. Extracting these features from μCT and μMRI images is difficult and measurements vary substantially according to image processing technique used. In this paper, we propose a fuzzy distance transform (FDT) method to measure trabecular bone thickness based on Min-Max operations and using an additive weighting term. Due to the employed fuzzy Min-Max operations along with the additive weighing term, the FDT method is performed in integer number space to consequently produce a computationally fast, robust and efficient use of memory method with taking into account the gray level of pixels. This method has been used to measure the trabecular thickness of bone samples with different bone volume fractions (BVF). Additionally, its performance was studied considering parameters such as image resolution, object rotation, noise and running time. The algorithm has proven to be very robust, precise and faster.

Variations in trabecular bone texture are known to be correlated with bone diseases, such as osteoporosis. In this paper we propose a multi-feature multi-ROI (MFMR) approach for analyzing trabecular patterns inside the oral cavity using cone beam computed tomography (CBCT) volumes. For each dental CBCT volume, a set of features including fractal dimension, multi-fractal spectrum and gradient based features are extracted from eight regions-ofinterest (ROI) to address the low image quality of trabecular patterns. Then, we use generalized multi-kernel learning (GMKL) to effectively fuse these features for distinguishing trabecular patterns from different groups. To validate the proposed method, we apply it to distinguish trabecular patterns from different gender-age groups. On a dataset containing dental CBCT volumes from 96 subjects, divided into gender-age subgroups, our approach achieves 96.1% average classification rate, which greatly outperforms approaches without the feature fusion.

Bone marrow was assumed with little effect on the bone mechanical property. As a result, there is no simulation model of bone strength considering bone marrow. While, it has been reported that fat marrow content increased in osteoporotic bone. Whether the fat marrow influences the bone mechanical property is unknown yet. Therefore, the objective of this study was to figure out the contribution of bone marrow fat in bone strength. A finite element model was established by using quantitative computed tomographic (QCT) data from a 63-year-old female's L3 vertebrae. With mechanical load applied on the finite element model, a significant higher maximum stress was observed in the model without bone marrow, compared to the one with fat marrow. The results indicated that bone marrow fat diminish the maximum stress on the trabecular bone and may function as a force buffer in a bone.

Adult bone diseases, especially osteoporosis, lead to increased risk of fracture associated with substantial morbidity, mortality, and financial costs. Clinically, osteoporosis is defined by low bone mineral density; however, increasing evidence suggests that the micro-architectural quality of trabecular bone (TB) is an important determinant of bone strength and fracture risk. Skeletonization plays an important role providing a compact representation of TB network that allows computation of several quantitative parameters relating to TB micro-architecture. Literature of three-dimensional skeletonization is quite matured for binary digital objects. However, the challenges of skeletonization for fuzzy objects are mostly unanswered. Here, an algorithm for fuzzy skeletonization is presented using fuzzy grassfire propagation and a branch-level noise pruning strategy and, finally, its application to TB micro-architectural assessment is investigated. Specifically, the fuzzy skeletonization algorithm is applied to compute TB plateness, plate/rod ratio, thickness, and spacing. Finally, the effectiveness of these measures to predict experimental bone strength is investigated on twelve cadaveric specimens and the results are encouraging with the R(2) value of linear correlation with bone strength being as high as 0.93, 0.88, 0.85 and 0.86, respectively.

The average BV/TV, TB.Th and Tb.Sp for the trabecular bone are 0.154±0.052, 0.203±0.025 mm and 0.812±0.151 mm, respectively. After normalization with sample thickness, the average normalized BUA (nBUA) is 24.8±9.5 dB/MHz/cm and 19.2±5.5 dB/MHz/cm for PS and PI respectively. PS nBUA is significantly different than PI BUA (paired t-test, p

International audience; Imaging of the trabecular bone network has made significant advances in the last decade thanks to the outstanding development of 3D X-ray micro-CT. Compared to standard histomorphometry, this technique provides non-destructively 3D images of the trabecular bone permitting a so-called model-independent quantification of this network. Today, the assessment of the bone Lacuno-Canalicular Network (LCN) is a new challenge at the cellular scale. The LCN forms a communication network interconnecting the osteocytes, the bone cells embedded in the mineralized matrix. It plays a major role in mechanotransduction with important implications on bone remodeling and finally bone strength. However, methods for the 3D assessment of the LCN are lacking. In a recent work, we have shown the feasibility of imaging the LCN in 3D thanks to Synchrotron Radiation nano-CT (voxel size 280 nm). These first images of the LCN in 3D open new challenges in image processing to segment and quantify the LCN. After recalling the principle of image acquisition, we present our first approaches for enhancing the contrast of canaliculi and segmenting the LCN. Finally, to increase the connectivity of the network, we consider a new approach based on 3D geodesic voting, offering promising perspectives. Results on experimental 3D images of the 3D LCN in human femoral bone are presented.

Trabecular bone has traditionally been assumed to be composed of plate- and rod-like trabeculae. This paper proposes a method to numerically evaluate the appropriateness of this assumption. In a first step, local constancy of thickness is estimated by comparing the maximum and mean diameter of the maximum inscribed balls centered at the medial axis/surface that includes every local point. In a second step, deviations from null curvature at the medial axis/surface are locally measured by comparing the geodesic and Euclidean distances from a point to its neighbors in the medial axis/surface. Finally, these two measurements are combined in order to locally estimate the compliance of the dataset with the plate-rod model assumption. Experiments on synthetic datasets show that the proposed measurements can be used to decide the compliance of a 3D shape with the plate-rod model. Results on micro computed tomography images show that the plate-rod model is more valid for a vertebra than for a radius. Thus, especially for the radius, measurements based on this model should be complemented with the proposed measurements.

We are developing a microwave imaging system for interrogating the calcaneus bone as a way of monitoring bone health progression in diseases such as osteoporosis We have previously shown that the dielectric properties of trabecular bone correspond well to the associated bone volume fraction which can be used as a good indicator of fracture risk. We present 3D results showing that the technique is sophisticated enough to recover the pertinent structures and that ultimately this technique will be sufficiently sensitive for disease monitoring

The segmentation of biomedical images is a required stage for the quantification of biomedical features. In micro-CT images the segmentation of the scanned datasets is required in order to compute the morphometrical characteristics of the tissue structure. In literature the use of a fixed threshold, selected by means of different evaluation techniques, is usually suggested for this kind of images, but limits and critical scenarios were already highlighted. Different active segmentation methods were already suggested in literature for different biomedical purpose. Aim of the present study is the application of the Chan-Vese active segmentation technique to micro-CT images, and its comparison to the fixed threshold technique. Three micro-CT trabecular datasets were selected. The two segmentation techniques (Chan-Vese and fixed threshold) were applied and morphometrical parameters were computed for both of them. For every slice of every dataset, two dimentional (2D) bone density and trabecular thickness were computed. The resulted were compared between the two segmentation techniques by means of a paired t-test. Moreover a visual comparison was performed. The two segmentation techniques showed statistically significant differences in the measured parameters. According to this preliminary study, the Chan-Vese segmentation technique produced better results than the global thresholding in term of visual inspection, in scenarios with critical low bone density. Negligible differences were observed in the high density dataset.

In this work, five local adaptive thresholding methods (named Bernsen, Niblack, Sauvola, Wellner and White) were evaluated to segment three-dimensional X-ray microtomographies (µCT). The basic objective was to use a computer algorithm to automatically quantify bone morphology. The performance of these methods was quantitatively evaluated by using 128 images (pixel size of 0.015 mm) obtained from a three-dimensional numerical phantom, which mimics the porosity of trabecular bone. Thereafter, standard histomorphometric parameters (bone-volume to total-volume ratio [BV/TV (%)], bone-surface to bone-volume ratio [BS/BV (mm−1)], trabecular thickness [Tb.Th (µm)], trabecular number [Tb.N (mm−1)], and trabecular separation [Tb.Sp (µm)]) were estimated and usad as a means of comparison between the true segmentation values (obtained from the numerical phantom) and the outcome of each binarization algorithm. The results pointed out that Wellner method presented in general smaller errors than the other ones. The next step is to apply this method on real µCT for quantifying bone morphology.

Osteoporosis is a low bone mass oriented disease which can be diagnosed by measuring bone mineral density (BMD). Dual energy x-ray absorptiometry (DXA) method is considered as ‘gold’ standard for measuring BMD. WHO has defined a diagnostic criterion for the disease, based on DXA-BMD measurement at proximal femur and spine. In India, it is highly prevalent in post menopausal women and elderly subjects of both the sexes. The diseases related to hip and spine often equated with significant amount of mortality and morbidity. Fracture prevention, before its happening is the need of the hour. The DXA measures only areal BMD (g. cm-2), whereas it always bypasses the geometry and micro architecture of the bone. The aim of the proposed study was to test the potentiality of energy of the trabecular bone of the proximal femur that has been measured using Dual-tree complex wavelet transform (DT-CWT) in the evaluation of post-menopausal osteoporosis, when comparing with DXA as ‘gold’ standard. DXA-BMD of the right proximal femur of 50 (n=50, mean ± SD age = 50.1 ± 13.7 years) south Indian women aged above 25 years was measured. WHO criteria was used in all women; a standard digital x-ray of the right proximal femur was obtained and DT-CWT was carried out in two different approaches.

The objective of this study is to investigate the combined effects of micro-modeling (modeling reduces to a trivial level in maturity) and remodeling on the development of trabecular bone with aging or during menopause. The adaptation of trabecular bone involves modeling and remodeling processes. Although many models have been made to investigate the process of bone adaptation and provide insight into understanding of it, they failed to distinguish really bone modeling from remodeling. In our study, the computational model was divided into micro-modeling and remodeling components. Micro-modeling component was responsible for the net increase or decrease of trabeculae density; while remodeling component employed microdamage that distribute randomly within bone tissue as stimuli to initiate Basic Multicellular Units to replace and repair damaged tissue. Finally, the combined model was applied in conjunction with finite element method to a two-dimensional simulated trabecular bone structure. During the simulation, the developments in bone microstructure and material properties have been monitored. The results suggested that trabecular bone deteriorated and became anisotropy inevitably in elder individuals or post-menopause women. This work provides a novel methodology for the numerical simulation of bone morphological changes under the regulatory of biological-mechanical factors.

Three-dimensional X-Ray Micromotomography (3D µCT) has become an important tool to investigate bone morphology. Several investigators have searched a standard method for determining the optimal threshold value (optimal TH) to segment microtomographic images and quantify the bone morphology. The Conventional methods are based on subjective methods, and it is possible to obtain under or overestimated TH values. In this work, two automatic methods for segmenting 3D µCT are presented. The first one is based on Morphological Filters and Otsu's method (MFO), and the other one is based Artificial Ant Colony (AAC). Both method performances are evaluated quantitatively using a numerical phantom which mimics a trabecular bone. Besides, the proposed methods are applied to segment a microtomographic image from a rat vertebral bone. The segmented image of phantom based on AAC method showed results closer to the binary reference image of the numerical phantom and the histomorphometric parameters values presented smaller error (11.3%) than the one based on MFO (22.4%). When the methods were applied to segment a microtomographic image, the performances were compatible, and the histomorphometric parameter values present differences inferior to 9%.

The aim of this work was to characterize the periodicity of a commercial available trabecular bone phantom with ultrasound (US) backscattered signals. Three US frequencies were applied (1.0, 2.25 and 5.0 MHz), and spectral analysis methods were used to estimate the mean scatterer spacing (MSS) of 100 signals/sample from five different samples. The results showed that it is possible to estimate the medium periodicity (trabecular spacings varying from 1.5 to 2.5 mm), and at higher frequencies the average MSS decreased, which is expected because of a higher spatial resolution (identification of the trabecular thickness periodicity). MSS values are in agreement with intertrabecular distances declared by the product supplier.

Periodicity of structures can be investigated with backscattered ultrasound, usually by applying spectral methods and estimating the Mean Scatterer Spacing (MSS). Biological tissues, such as skeletal muscle, or liver or trabecular bone, can present periodic or quasi-periodic structures. In this work it is studied the behavior of MSS with temperature and frequency for in vitro samples of bovine muscular tissues. MSS was obtained in the range of 37oC to 43oC, and between 1 MHz to 10.0 MHz Results show that, for the studied sample, MSS decreased with temperature for the muscle. It seems to be in agreement with the expected physiologic behavior of muscular fibers. Further complementary experiments are being envisaged.