• Korean Journal of Computational Design and Engineering
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• v.16 no.6
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• pp.458-466
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• 2011

The morphology of a bone is closely associated with its biomechanical response. Thus, much research has been focused on analyzing the effects of variation of bone morphology with subject-specific models. Subject-specific models, which are generally achieved from 3D imaging devices like CT and MRI, incorporate more of the detailed information that makes a model unique. Hence, it may predict individual responses more accurately. Despite these powerful characteristics, specific models are not easily parameterized to the extent possible with statistical models because of their morphologic complexities. Thus, it is still proven challenging to analyze morphologic variations of subject-specific models across changes due to aging or disease. The aim of this article is to propose a generic and robust parametric morphing method for a subject-specific bone structure. We demonstrate this by using the proposed method on a model of a human proximal femur. Automatic segmentation algorithms are also presented to parameterize the specific model efficiently. A total of 48 femur models were evaluated for defining morphing vector fields. Also, several anatomical and mechanical functions of femur were considered as morphing constraints, and the NURBS interpolating technique was applied in the method to guarantee the generality of our morphed results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.10
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• pp.1139-1145
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• 2014

Creation of a human skeleton model and characterization of the variation in the bone shape are fundamentally important in many applications of biomechanics. In this paper, we present a parametric shape modeling method for femurs that is based on extracting the main parameter of variations of the femur shape from a 3D model database by using statistical shape analysis. For this shape analysis, principal component analysis (PCA) is used. Application of the PCA to 3D data requires bringing all the models in correspondence to each other. For this reason, anatomical landmarks are used for guiding the deformation of the template model to fit the 3D model data. After subsequent application of PCA to a set of femur models, we calculate the correlation between the dominant components of shape variability for a target population and the anatomical parameters of the femur shape. Finally, we provide tools for visualizing and creating the femur shape using the main parameter of femur shape variation.

• Journal of Biomedical Engineering Research
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• v.20 no.2
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• pp.155-164
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• 1999

In this paper, the prototype of SIS(Simulated Implantation System) for human femoral head is introduced. SIS is a software which carries on a virtual femoral head replacement surgery including 3d visualization as well as various numeric analyses between a patient's femur and artificial femur through certain stages of the image processing and of the computer graphics. Also, processes required after acquiring consecutive CT-images and projected image of an artificial femur are discussed, and the corresponding results including prototype of SIS are given.

• Journal of Biomedical Engineering Research
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• v.15 no.2
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• pp.183-188
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• 1994

In clinical orthopaedics, bone resoption in the cortex is often seen post operatively on X-rays or bone densitometry after total hip replacement (THR) in the form of cortical osteoporosis or atropy. Stress shielding of bone occurs, when a load, normally carried by the bone alone, is shared with an implant as a result, the bone stresses are abnormal and with remodelling analysis this may cause extensive proximal bone resoption, possibly weakening the bone bed to the point of failure. The author made finite element models of the cemented and non-cemented type implanted femoral stem with bone resorption of the proximal medial femur and studied the feed back effect of the various degree of bone resoption to THR system by parametric analysis on the stress of the femoral stem and interface. The results of the present finite element analysis implied that the extent of proximal bone resorption has the effect of more increasing stress on the distal stem tip, cement mantle and interface in both type of femoral stem and this high distal stress possibly can cause the mechanical failure of loosening or failure after THR.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.317-325
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• 2007

Purpose: Biological parameters can be quantified using dynamic PET data with compartment modeling and Nonlinear Least Square (NLS) estimation. However, the generation of parametric images using the NLS is not appropriate because of the initial value problem and excessive computation time. In irreversible model, Patlak graphical analysis (PGA) has been commonly used as an alternative to the NLS method. In PGA, however, the start time ($t^*$, time where linear phase starts) has to be determined. In this study, we suggest a new Multiple Linear Analysis for irreversible radiotracer (MLAIR) to estimate fluoride bone influx rate (Ki). Methods: $[^{18}F]Fluoride$ dynamic PET scans was acquired for 60 min in three normal mini-pigs. The plasma input curve was derived using blood sampling from the femoral artery. Tissue time-activity curves were measured by drawing region of interests (ROls) on the femur head, vertebra, and muscle. Parametric images of Ki were generated using MLAIR and PGA methods. Result: In ROI analysis, estimated Ki values using MLAIR and PGA method was slightly higher than those of NLS, but the results of MLAIR and PGA were equivalent. Patlak slopes (Ki) were changed with different $t^*$ in low uptake region. Compared with PGA, the quality of parametric image was considerably improved using new method. Conclusion: The results showed that the MLAIR was efficient and robust method for the generation of Ki parametric image from $[^{18}F]Fluoride$ PET. It will be also a good alternative to PGA for the radiotracers with irreversible three compartment model.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.5
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• pp.459-465
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• 2011

It has been reported that the femoral morphology has a major correlation to femoral neck fractures(FNF). Previous studies to analyze these correlations have relied on mechanical testing and finite element methods. However, these methods have not been widely applied to various femur samples and models. It is because of the availability of the samples from both patients and cadavers, and also of the geometric limitations in changing the shape of the models. In this study we analyzed femoral neck fractures using a parameterized femoral model that could provide flexibility in changing the geometry of the model for the wide applications of FNF analysis. With the parameterization a variety of models could be generated by changing four major dimensions: femoral head diameter(FHD), femoral neck diameter(FND), femoral neck length(FNL), and neck-shaft angle(NSA). We have performed FEA on the models to compute the stress distributions and reaction forces, and compare them with the data previously generated from mechanical testing. The analysis results indicate that the FND is significantly related with the FNF and the FHD is not significantly related with the FNF.