Mesh-morphing algorithms for specimen-specific finite element modeling

Despite recent advances in software for meshing specimen-specific geometries, considerable effort is still often required to produce and analyze specimen-specific models suitable for biomechanical analysis through finite element modeling. We hypothesize that it is possible to obtain accurate models by adapting a pre-existing geometry to represent a target specimen using morphing techniques. Here we present two algorithms for morphing, automated wrapping (AW) and manual landmarks (ML), and demonstrate their use to prepare specimen-specific models of caudal rat vertebrae. We evaluate the algorithms by measuring the distance between target and morphed geometries and by comparing response to axial loading simulated with finite element (FE) methods.

First a traditional reconstruction process based on μCT was used to obtain two natural specimen-specific FE models. Next, the two morphing algorithms were used to compute mappings from the surface of one model, the source, to the other, the target, and to use this mapping to morph the source mesh to produce a target mesh. The μCT images were then used to assign element-specific material properties. In AW the mappings were obtained by wrapping the source and target surfaces with an auxiliary triangulated surface. In ML, landmarks were manually placed on corresponding locations on the surfaces of both source and target.

Both morphing algorithms were successful in reproducing the shape of the target vertebra with a median distance between natural and morphed models of 18.8 and 32.2 μm, respectively, for AW and ML. Whereas AW–morphing produced a surface more closely resembling that of the target, ML guaranteed correspondence of the landmark locations between source and target. Morphing preserved the quality of the mesh producing models suitable for FE simulation. Moreover, there were only minor differences between natural and morphed models in predictions of deformation, strain and stress. We therefore conclude that it is possible to use mesh-morphing techniques to produce accurate specimen-specific FE models of caudal rat vertebrae. Mesh morphing techniques provide advantages over conventional specimen-specific finite element modeling by reducing the effort required to generate multiple target specimen models, facilitating intermodel comparisons through correspondence of nodes and maintenance of connectivity, and lends itself to parametric evaluation of “artificial” geometries with a focus on optimizing reconstruction.     

Analysis of pelvic strain in different gait configurations in a validated cohort of computed tomography based finite element models

The pelvis functions to transmit upper body loads to the lower limbs and is critical in human locomotion. Semi-automated, landmark-based finite element (FE) morphing and mapping techniques eliminate the need for segmentation and have shown to accelerate the generation of multiple specimen-specific pelvic FE models to enable the study of pelvic mechanical behaviour. The purpose of this research was to produce an experimentally validated cohort of specimen-specific FE models of the human pelvis and to use this cohort to analyze pelvic strain patterns during gait. Using an initially segmented specimen-specific pelvic FE model as a source model, four more specimen-specific pelvic FE models were generated from target clinical CT scans using landmark-based morphing and mapping techniques. FE strains from the five models were compared to the experimental strains obtained from cadaveric testing via linear regression analysis, (R² values ranging from 0.70 to 0.93). Inter-specimen variability in FE strain distributions was seen among the five specimen-specific pelvic FE models. The validated cohort of specimen-specific pelvic FE models was utilized to examine pelvic strains at different phases of the gait cycle. Each validated specimen-specific FE model was reconfigured into gait cycle phases representing heel-strike/heel-off and midstance/midswing. No significant difference was found in the double-leg stance and heel-strike/heel-off models (p = 0.40). A trend was observed between double-leg stance and midstance/midswing models (p = 0.07), and a significant difference was found between heel-strike/heel-off models and midstance/midswing models (p = 0.02). Significant differences were also found in comparing right vs. left models (heel-strike/heel-off p = 0.14, midstance/midswing p = 0.04).     

The influence of material property and morphological parameters on specimen-specific finite element models of porcine vertebral bodies

The use of finite element (FE) methods in spinal research is increasing, but there is only limited information available on the influence of different input parameters on the model predictions. The aim of this study was to investigate the role of these parameters in FE models of the vertebral body. Experimental tests were undertaken on porcine lumbar vertebral bodies and scans of the specimens were used to create specimen-specific FE models. Three models were created for each specimen with combinations of generic and specimen-specific parameters. Stiffness and strength predictions were also made directly from the specimen trabecular bone volume fraction (BVF) and cross-sectional area (CSA). The agreement between the experimental results and the FE models with generic morphology was poorer (concordance coefficients = 0.058, 0.125 for stiffness, strength) than those made from the BVF and CSA (concordance coefficients = 0.638, 0.609). The greatest levels of agreement were found with the morphologically specific models including element-specific material properties (concordance coefficients = 0.881, 0.752). This indicates that highly specific models, both in terms of morphology and bone quality, are necessary if the FE tool is to be used effectively for spinal research and clinical practice.     

A Comprehensive Specimen-Specific Multiscale Data Set for Anatomical and Mechanical Characterization of the Tibiofemoral Joint

Understanding of tibiofemoral joint mechanics at multiple spatial scales is essential for developing effective preventive measures and treatments for both pathology and injury management. Currently, there is a distinct lack of specimen-specific biomechanical data at multiple spatial scales, e.g., joint, tissue, and cell scales. Comprehensive multiscale data may improve the understanding of the relationship between biomechanical and anatomical markers across various scales. Furthermore, specimen-specific multiscale data for the tibiofemoral joint may assist development and validation of specimen-specific computational models that may be useful for more thorough analyses of the biomechanical behavior of the joint. This study describes an aggregation of procedures for acquisition of multiscale anatomical and biomechanical data for the tibiofemoral joint. Magnetic resonance imaging was used to acquire anatomical morphology at the joint scale. A robotic testing system was used to quantify joint level biomechanical response under various loading scenarios. Tissue level material properties were obtained from the same specimen for the femoral and tibial articular cartilage, medial and lateral menisci, anterior and posterior cruciate ligaments, and medial and lateral collateral ligaments. Histology data were also obtained for all tissue types to measure specimen-specific cell scale information, e.g., cellular distribution. This study is the first of its kind to establish a comprehensive multiscale data set for a musculoskeletal joint and the presented data collection approach can be used as a general template to guide acquisition of specimen-specific comprehensive multiscale data for musculoskeletal joints.     

Combining specimen-specific finite-element models and optimization in cortical-bone material characterization improves prediction accuracy in three-point bending tests

Although the beam theory is widely used for calculating material parameters in three-point bending test, it cannot accurately describe the biomechanical properties of specimens after the yield. Hence, we propose a finite element (FE) based optimization method to obtain accurate bone material parameters from three-point bending test. We tested 80 machined bovine cortical bone specimens at both longitudinal and transverse directions using three-point bending. We then adopted the beam theory and the FE-based optimization method combined with specimen-specific FE models to derive the material parameters of cortical bone. We compared data obtained using these two methods and further evaluated two groups of parameters with three-point bending simulations. Our data indicated that the FE models with material properties from the FE-based optimization method showed best agreements with experimental data for the entire force-displacement responses, including the post-yield region. Using the beam theory, the yield stresses derived from 0.0058% strain offset for the longitudinal specimen and 0.0052% strain offset for the transverse specimen are closer to those derived from the FE-based optimization method, compared to yield stresses calculated without strain offset. In brief, we conclude that the optimization FE method is more appropriate than the traditional beam theory in identifying the material parameters of cortical bone for improving prediction accuracy in three-point bending mode. Given that the beam theory remains as a popular method because of its efficiency, we further provided correction functions to adjust parameters calculated from the beam theory for accurate FE simulation.     

Morphing the feature-based multi-blocks of normative/healthy vertebral geometries to scoliosis vertebral geometries: development of personalized finite element models

Personalized Finite Element (FE) models and hexahedral elements are preferred for biomechanical investigations. Feature-based multi-block methods are used to develop anatomically accurate personalized FE models with hexahedral mesh. It is tedious to manually construct multi-blocks for large number of geometries on an individual basis to develop personalized FE models. Mesh-morphing method mitigates the aforementioned tediousness in meshing personalized geometries every time, but leads to element warping and loss of geometrical data. Such issues increase in magnitude when normative spine FE model is morphed to scoliosis-affected spinal geometry. The only way to bypass the issue of hex-mesh distortion or loss of geometry as a result of morphing is to rely on manually constructing the multi-blocks for scoliosis-affected spine geometry of each individual, which is time intensive. A method to semi-automate the construction of multi-blocks on the geometry of scoliosis vertebrae from the existing multi-blocks of normative vertebrae is demonstrated in this paper. High-quality hexahedral elements were generated on the scoliosis vertebrae from the morphed multi-blocks of normative vertebrae. Time taken was 3 months to construct the multi-blocks for normative spine and less than a day for scoliosis. Efforts taken to construct multi-blocks on personalized scoliosis spinal geometries are significantly reduced by morphing existing multi-blocks.     

3D characterization of bone strains in the rat tibia loading model

Bone strain is considered one of the factors inducing bone tissue response to loading. Nevertheless, where animal studies can provide detailed data on bone response, they only offer limited information on experimental bone strains. Including micro-CT-based finite element (micro FE) models in the analysis represents a potent methodology for quantifying strains in bone. Therefore, the main objective of this study was to develop and validate specimen-specific micro FE models for the assessment of bone strains in the rat tibia compression model. Eight rat limbs were subjected to axial compression loading; strain at the medio-proximal site of the tibiae was measured by means of strain gauges. Specimen-specific micro FE models were created and analyzed. Repeated measurements on each limb indicated that the effect of limb positioning was small (COV?= 6.45 ± 2.27 %). Instead, the difference in the measured strains between the animals was high (54.2%). The computational strains calculated at the strain gauge site highly correlated to the measured strains (R ²?=?0.95). Maximum peak strains calculated at exactly 25% of the tibia length for all specimens were equal to 435.11 ± 77.88 microstrains (COV?=?17.19%). In conclusion, we showed that strain gauge measurements are very sensitive to the exact strain gauge location on the bone; hence, the use of strain gauge data only is not recommended for studies that address at identifying reliable relationships between tissue response and local strains. Instead, specimen-specific micro FE models of rat tibiae provide accurate estimates of tissue-level strains.     

An eFTD-VP framework for efficiently generating patient-specific anatomically detailed facial soft tissue FE mesh for craniomaxillofacial surgery simulation

Accurate surgical planning and prediction of craniomaxillofacial surgery outcome requires simulation of soft tissue changes following osteotomy. This can only be achieved by using an anatomically detailed facial soft tissue model. The current state-of-the-art of model generation is not appropriate to clinical applications due to the time-intensive nature of manual segmentation and volumetric mesh generation. The conventional patient-specific finite element (FE) mesh generation methods are to deform a template FE mesh to match the shape of a patient based on registration. However, these methods commonly produce element distortion. Additionally, the mesh density for patients depends on that of the template model. It could not be adjusted to conduct mesh density sensitivity analysis. In this study, we propose a new framework of patient-specific facial soft tissue FE mesh generation. The goal of the developed method is to efficiently generate a high-quality patient-specific hexahedral FE mesh with adjustable mesh density while preserving the accuracy in anatomical structure correspondence. Our FE mesh is generated by eFace template deformation followed by volumetric parametrization. First, the patient-specific anatomically detailed facial soft tissue model (including skin, mucosa, and muscles) is generated by deforming an eFace template model. The adaptation of the eFace template model is achieved by using a hybrid landmark-based morphing and dense surface fitting approach followed by a thin-plate spline interpolation. Then, high-quality hexahedral mesh is constructed by using volumetric parameterization. The user can control the resolution of hexahedron mesh to best reflect clinicians’ need. Our approach was validated using 30 patient models and 4 visible human datasets. The generated patient-specific FE mesh showed high surface matching accuracy, element quality, and internal structure matching accuracy. They can be directly and effectively used for clinical simulation of facial soft tissue change.     

Specimen-specific predictions of contact stress under physiological loading in the human hip: validation and sensitivity studies

Hip osteoarthritis may be initiated and advanced by abnormal cartilage contact mechanics, and finite element (FE) modeling provides an approach with the potential to allow the study of this process. Previous FE models of the human hip have been limited by single specimen validation and the use of quasi-linear or linear elastic constitutive models of articular cartilage. The effects of the latter assumptions on model predictions are unknown, partially because data for the instantaneous behavior of healthy human hip cartilage are unavailable. The aims of this study were to develop and validate a series of specimen-specific FE models, to characterize the regional instantaneous response of healthy human hip cartilage in compression, and to assess the effects of material nonlinearity, inhomogeneity and specimen-specific material coefficients on FE predictions of cartilage contact stress and contact area. Five cadaveric specimens underwent experimental loading, cartilage material characterization and specimen-specific FE modeling. Cartilage in the FE models was represented by average neo-Hookean, average Veronda Westmann and specimen- and region-specific Veronda Westmann hyperelastic constitutive models. Experimental measurements and FE predictions compared well for all three cartilage representations, which was reflected in average RMS errors in contact stress of less than 25 %. The instantaneous material behavior of healthy human hip cartilage varied spatially, with stiffer acetabular cartilage than femoral cartilage and stiffer cartilage in lateral regions than in medial regions. The Veronda Westmann constitutive model with average material coefficients accurately predicted peak contact stress, average contact stress, contact area and contact patterns. The use of subject- and region-specific material coefficients did not increase the accuracy of FE model predictions. The neo-Hookean constitutive model underpredicted peak contact stress in areas of high stress. The results of this study support the use of average cartilage material coefficients in predictions of cartilage contact stress and contact area in the normal hip. The regional characterization of cartilage material behavior provides the necessary inputs for future computational studies, to investigate other mechanical parameters that may be correlated with OA and cartilage damage in the human hip. In the future, the results of this study can be applied to subject-specific models to better understand how abnormal hip contact stress and contact area contribute to OA.     

A visco-elastic model for the prediction of orthodontic tooth movement

This study presents a biomechanical model of orthodontic tooth movement. Although such models have already been presented in the literature, most of them incorporate computationally expensive finite elements (FE) methods to determine the strain distribution in the periodontal ligament (PDL). In contrast, the biomechanical model presented in this work avoids the use of FE methods. The elastic deformation of the PDL is modelled using an analytical approach, which does not require setting up a 3D model of the tooth. The duration of the lag phase is estimated using the calculated hydrostatic stresses, and bone remodelling is predicted by modelling the alveolar bone as a viscous material. To evaluate the model, some typically used motion patterns were simulated and a sensitivity analysis was carried out on the parameters. Results show that despite some shortcomings, the model is able to describe commonly used motion patterns in orthodontic tooth movement, in both single- and multi-rooted teeth.     

The influence of ligament modelling strategies on the predictive capability of finite element models of the human knee joint

In finite element (FE) models knee ligaments can represented either by a group of one-dimensional springs, or by three-dimensional continuum elements based on segmentations. Continuum models closer approximate the anatomy, and facilitate ligament wrapping, while spring models are computationally less expensive. The mechanical properties of ligaments can be based on literature, or adjusted specifically for the subject. In the current study we investigated the effect of ligament modelling strategy on the predictive capability of FE models of the human knee joint. The effect of literature-based versus specimen-specific optimized material parameters was evaluated. Experiments were performed on three human cadaver knees, which were modelled in FE models with ligaments represented either using springs, or using continuum representations. In spring representation collateral ligaments were each modelled with three and cruciate ligaments with two single-element bundles. Stiffness parameters and pre-strains were optimized based on laxity tests for both approaches. Validation experiments were conducted to evaluate the outcomes of the FE models.Models (both spring and continuum) with subject-specific properties improved the predicted kinematics and contact outcome parameters. Models incorporating literature-based parameters, and particularly the spring models (with the representations implemented in this study), led to relatively high errors in kinematics and contact pressures. Using a continuum modelling approach resulted in more accurate contact outcome variables than the spring representation with two (cruciate ligaments) and three (collateral ligaments) single-element-bundle representations. However, when the prediction of joint kinematics is of main interest, spring ligament models provide a faster option with acceptable outcome.     

Finite element and experimental cortex strains of the intact and implanted tibia

Finite Element (FE) models for the simulation of intact and implanted bone find their main purpose in accurately reproducing the associated mechanical behavior. FE models can be used for preclinical testing of joint replacement implants, where some biomechanical aspects are difficult, if not possible, to simulate and investigate in vitro. To predict mechanical failure or damage, the models should accurately predict stresses and strains. Commercially available synthetic femur models have been extensively used to validate finite element models, but despite the vast literature available on the characteristics of synthetic tibia, numerical and experimental validation of the intact and implant assemblies of tibia are very limited or lacking. In the current study, four FE models of synthetic tibia, intact and reconstructed, were compared against experimental bone strain data, and an overall agreement within 10% between experimental and FE strains was obtained. Finite element and experimental (strain gauge) models of intact and implanted synthetic tibia were validated based on the comparison of cortex bone strains. The study also includes the analysis carried out on standard tibial components with cemented and noncemented stems of the P.F.C Sigma Modular Knee System. The overall agreement within 10% previously established was achieved, indicating that FE models could be successfully validated. The obtained results include a statistical analysis where the root-mean-square-error values were always <10%. FE models can successfully reproduce bone strains under most relevant acting loads upon the condylar surface of the tibia. Moreover, FE models, once properly validated, can be used for preclinical testing of tibial knee replacement, including misalignment of the implants in the proximal tibia after surgery, simulation of long-term failure according to the damage accumulation failure scenario, and other related biomechanical aspects.     

The use of preserved tissue in finite element modelling of fresh ovine vertebral behaviour

The aim of this study was to investigate whether the predicted finite element (FE) stiffness of vertebral bone is altered when using images of preserved rather than fresh tissue to generate specimen-specific FE models. Fresh ovine vertebrae were used to represent embalmed (n = 3) and macerated dry-bone (n = 3) specimens and treated accordingly. Specimens were scanned pre- and post-treatment using micro-computed tomography. A constant threshold level derived from these images was used to calculate the respective bone volume fraction (BV/TV) from which the conversion factor validated for fresh tissue was used to determine material properties that were assigned to corresponding FE models. Results showed a definite change in the BV/TV between the fresh and the preserved bone. However, the changes in the predicted FE stiffness were not generally greater than the variations expected from assignment of loading and boundary conditions. In conclusion, images of preserved tissue can be used to generate FE models that are representative of fresh tissue with a tolerable level of error.     

Effects of obesity on occupant responses in frontal crashes: a simulation analysis using human body models

The objective of this study is to investigate the effects of obesity on occupant responses in frontal crashes using whole-body human finite element (FE) models representing occupants with different obesity levels. In this study, the geometry of THUMS 4 midsize male model was varied using mesh morphing techniques with target geometries defined by statistical models of external body contour and exterior ribcage geometry. Models with different body mass indices (BMIs) were calibrated against cadaver test data under high-speed abdomen loading and frontal crash conditions. A parametric analysis was performed to investigate the effects of BMI on occupant injuries in frontal crashes based on the Taguchi method while controlling for several vehicle design parameters. Simulations of obese occupants predicted significantly higher risks of injuries to the thorax and lower extremities in frontal crashes compared with non-obese occupants, which is consistent with previous field data analyses. These higher injury risks are mainly due to the increased body mass and relatively poor belt fit caused by soft tissues for obese occupants. This study demonstrated the feasibility of using a parametric human FE model to investigate the obesity effects on occupant responses in frontal crashes.     

Factors affecting subject-specific finite element models of implant-fitted rat bone specimens: critical analysis of a technical protocol

The authors propose a protocol to derive finite element (FE) models from micro computer tomography scans of implanted rat bone. A semi-automatic procedure allows segmenting the images using specimen-specific bone mineral density (BMD) thresholds. An open-source FE model generator processes the segmented images to a quality tetrahedral mesh. The material properties assigned to each element are integrated from the BMD field. Piecewise, threshold-dependent density–elasticity relationships are implemented to limit the effects of metal artefacts. A detailed sensitivity study highlights the coherence of the generated models and quantifies the influence of the modelling parameters on the results. Two applications of the protocol are proposed. The stiffness of bare and implanted rat tibiae specimens is predicted by simulating three-point bending and inter-implant displacement, respectively. Results are compared with experimental tests. The mean value and the variability between the specimens are well captured in both tests.     

Comparison of methods to determine the centre of resistance of teeth

In orthodontic treatment, the locations of the centre of resistance (CR) of individual teeth and the applied load system are the major determinants for the type of tooth movement achieved. Currently, CR locations have only been specified for a relatively small number of tooth specimen for research purposes. Analysing cone beam computed tomography data samples from three upper central incisors, this study explores whether the effort to establish accurate CR estimates can be reduced by (i) morphing a pre-existing simplified finite element (FE) mesh to fit to the segmented 3D tooth-bone model, and (ii) individualizing a mean CR location according to a small parameter set characterising the morphology of the tooth and its embedding. The FE morphing approach and the semi-analytical approach led to CR estimates that differ in average only 0.04 and 0.12 mm respectively from those determined by very time-consuming individual FE modelling (standard method). Both approaches may help to estimate the movement of individual teeth during orthodontic treatment and, thus, increase the therapeutic efficacy.     

Finite element modeling of the human kidney for probabilistic occupant models: Statistical shape analysis and mesh morphing

Statistical shape analysis was conducted on 15 pairs (left and right) of human kidneys. It was shown that the left and right kidney were significantly different in size and shape. In addition, several common modes of kidney variation were identified using statistical shape analysis. Semi-automatic mesh morphing techniques have been developed to efficiently create subject specific meshes from a template mesh with a similar geometry. Subject specific meshes as well as probabilistic kidney meshes were created from a template mesh. Mesh quality remained about the same as the template mesh while only taking a fraction of the time to create the mesh from scratch or morph with manually identified landmarks. This technique can help enhance the quality of information gathered from experimental testing with subject specific meshes as well as help to more efficiently predict injury by creating models with the mean shape as well as models at the extremes for each principal component.     

Statistical shape modelling versus linear scaling: Effects on predictions of hip joint centre location and muscle moment arms in people with hip osteoarthritis

Marker-based dynamic functional or regression methods are used to compute joint centre locations that can be used to improve linear scaling of the pelvis in musculoskeletal models, although large errors have been reported using these methods. This study aimed to investigate if statistical shape models could improve prediction of the hip joint centre (HJC) location. The inclusion of complete pelvis imaging data from computed tomography (CT) was also explored to determine if free-form deformation techniques could further improve HJC estimates. Mean Euclidean distance errors were calculated between HJC from CT and estimates from shape modelling methods, and functional- and regression-based linear scaling approaches. The HJC of a generic musculoskeletal model was also perturbed to compute the root-mean squared error (RMSE) of the hip muscle moment arms between the reference HJC obtained from CT and the different scaling methods. Shape modelling without medical imaging data significantly reduced HJC location error estimates (11.4 ± 3.3 mm) compared to functional (36.9 ± 17.5 mm, p = <0.001) and regression (31.2 ± 15 mm, p = <0.001) methods. The addition of complete pelvis imaging data to the shape modelling workflow further reduced HJC error estimates compared to no imaging (6.6 ± 3.1 mm, p = 0.002). Average RMSE were greatest for the hip flexor and extensor muscle groups using the functional (16.71 mm and 8.87 mm respectively) and regression methods (16.15 mm and 9.97 mm respectively). The effects on moment-arms were less substantial for the shape modelling methods, ranging from 0.05 to 3.2 mm. Shape modelling methods improved HJC location and muscle moment-arm estimates compared to linear scaling of musculoskeletal models in patients with hip osteoarthritis.     

Characterization of craniofacial sutures using the finite element method

Characterizing the biomechanical behavior of sutures in the human craniofacial skeleton (CFS) is essential to understand the global impact of these articulations on load transmission, but is challenging due to the complexity of their interdigitated morphology, the multidirectional loading they are exposed to and the lack of well-defined suture material properties. This study aimed to quantify the impact of morphological features, direction of loading and suture material properties on the mechanical behavior of sutures and surrounding bone in the CFS. Thirty-six idealized finite element (FE) models were developed. One additional specimen-specific FE model was developed based on the morphology obtained from a µCT scan to represent the morphological complexity inherent in CFS sutures. Outcome variables of strain energy (SE) and von Mises stress (σ_vm) were evaluated to characterize the sutures’ biomechanical behavior. Loading direction was found to impact the relationship between SE and interdigitation index and yielded varied patterns of σ_vm in both the suture and surrounding bone. Adding bone connectivity reduced suture strain energy and altered the σ_vm distribution. Incorporating transversely isotropic material properties was found to reduce SE, but had little impact on stress patterns. High-resolution µCT scanning of the suture revealed a complex morphology with areas of high and low interdigitations. The specimen specific suture model results were reflective of SE absorption and σ_vm distribution patterns consistent with the simplified FE results. Suture mechanical behavior is impacted by morphologic factors (interdigitation and connectivity), which may be optimized for regional loading within the CFS.     

An image-based method to automatically propagate bony landmarks: application to computational spine biomechanics

In attempts to elucidate the underlying mechanisms of spinal injuries and spinal deformities, several experimental and numerical studies have been conducted to understand the biomechanical behavior of the spine. However, numerical biomechanical studies suffer from uncertainties associated with hard- and soft-tissue anatomies. Currently, these parameters are identified manually on each mesh model prior to simulations. The determination of soft connective tissues on finite element meshes can be a tedious procedure, which limits the number of models used in the numerical studies to a few instances. In order to address these limitations, an image-based method for automatic morphing of soft connective tissues has been proposed. Results showed that the proposed method is capable to accurately determine the spatial locations of predetermined bony landmarks. The present method can be used to automatically generate patient-specific models, which may be helpful in designing studies involving a large number of instances and to understand the mechanical behavior of biomechanical structures across a given population.