Geometrically accurate and anatomically correct threedimensional geometric models of human bones or bone sections are essential for successful pre-operative planning in orthopedic surgery. For such purposes, 3D polygonal models of bones are usually created based on Computer Tomography (CT) or Magnetic Resonance Imaging (MRI) data. In cases where there is no CT or MRI scan, or part of bone is missing, such three-dimensional polygonal models are difficult to create. In these situations predictive bone models are commonly used. In this paper, the authors describe the developed a software system for creation of Human Bones Customized Polygonal models (HBCP) which is based on the use of the predictive parametric bone model. The software system enables creation of patient-specific polygonal models of bones, by using only a limited number of parameter values. Parameter values can be acquired from volumetric medical imaging methods (CT, MRI), or from two-dimensional imaging methods (i.e. Xray). This paper introduces the new approach to the process of creation of human bones geometrical models which are based on the anatomical landmark points. Testing of the HBCP for the cases of femur bone samples has shown that created bone and bone region models are characterized by a good level of anatomical and morphometric accuracy compared to the results presented in similar researches.
A finite element (FE) model for analysis of tire rolling on the drum, based on a specially developed CAD model, is presented in the paper. All the changes performed on the geometry of CAD model are automatically propagated to FE model. This makes the FE model very suitable for parametric studies, which help tire designer to quickly find the optimal values of tire design parameters. In this way the tire design process is shortened and the quality of resulting tires improved. The results of finite element analyses conducted on the model have directly been compared to experimental ones, confirming model validity. Equipment and methods used for experimental determination of braking and cornering characteristics of the tire as well as for experimental determination of friction coefficient of tire tread have been shown. The difference between experimental and numerical results was smaller after the calibration of friction coefficient had been performed and in such a way a further improvement of the existing model was achieved.
Most certainly, in the field of medicine there is a great contribution of new techniques and technologies, which is reflected in an entire system of health care services. Customized implants are both fully geometrically and topologically adjusted so as to meet the needs of individual patients, thus making each implant unique. Their production requires joint efforts of a multidisciplinary team of different profile experts who combine their knowledge in the Implant knowledge model. Thus, we develop an expert system which should help or replace humans in the process of Implant material selection. This paper gives an overview of the expert system concept for the given problem. Its task is to carry out a selection of biomaterial (or class of material) for a customized implant. The model significantly improves the efficiency of preoperative planning in orthopaedics.
Computer-Assisted Orthopaedic Surgery (CAOS) defines a set of techniques that use computers and other devices for planning, guiding, and performing surgical interventions. The important components of CAOS are accurate geometrical models of human bones and plate implants, which can be used in preoperational planning or for surgical guiding during an intervention. Software framework which is introduced in this study is based on the Model-View-Controller (MVC) architectural pattern, and it uses 3D models of bones and plate implants developed by the application of the Method of Anatomical Features (MAF). The presented framework may be used for preoperative planning processes and for the production of personalized plate implants. The main idea of the research was to develop a novel integrated software framework which will provide improved personalized healthcare to the patient, and at the same time, provide the surgeon with more control over the patient's treatment and recovery.
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