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Objective To establish CT image-based, three-dimensional finite element models of healthy tibiae and plateau-fracture tibiae, and to calculate the displacement and stress distribution of the tibial models .Methods Continuous-time tomographic images of knee joints of a healthy adult and a patient with tibial plateau fractures were obtained using multi-slice spiral CT scan , and inputed to Mimics to establish three-dimensional surface mesh models of tibiae .The models underwent global meshing procedures and material properties assignment to construct finite element models of normal and plateau-fracture tibiae in ANSYS , and the newly established models were analyzed and calculated .Results In case of applied load on the tibial plateau , the peak strains of the load-contact sites in the healthy subject and the patient presented divergent directions , with peak strains on the medial tibia in the healthy subject and lateral tibia in the patient , respectively . Equivalent stress decreased gradually down the tibiae and concentrated in the one -third of the upper and middle regions in both types of tibiae .Moreover, concentration of stress was also present in the locus of the fractured tibia .The deformation displacement gradients were more evident in the healthy tibia than in the fractured tibiae .There was significant difference in overall stress distribution between the two types of tibiae .Conclusion Three-dimensional finite element models of tibiae have been established that can demonstrate the differences in biomechanical properties between healthy and plateau -fracture tibiae, which might provide reference and guidance for orthopedic regimens .
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Thrombelastography (TEG) is an image presenting the viscoelasticity changes of blood clot in the process of blood clotting,consequently reflecting the ability of blood clotting and fibrinolysis.TEG is increasingly used in the field of guiding intraoperative blood transfusion,monitoring the Blood coagulation function,treating trauma patient,and monitoring the blood coagulation and fibrinolytic function of a variety of diseases,due to its rapid and accurate results.We discuss the clinical applications progress of TEG in this article.
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Objective The hemodynamic mechanism of Budd-Chiari syndrome ( BCS ) has become the research hotspot in recent years.The aim of this study was to discuss the hemodynamic characteristics of BCS through 3D numerical simulation for inferior vena cava stenosis based on the fluid dynamics ( CFD) method. Methods 3D model was established from a patient with Budd-Chiari syndrome based on MR image with Ansys software .The numerical simulation of this model was performed by the CFD . Results The 3D model of inferior vena cava functionally demonstrated the change procedure of hemodynamic characteristics of BCS .Vortex was found above the narrow area , and blood flow velocity achieved maximum in the center of the stenosis throughout the coronal section graph.The static pressure value gradually declined at the narrow area entrance to the narrowest place , and achieved minimum value at the exit.The maximum wall shear stress existed in the stenosis . Conclusion Specific 3D computational hemodynamic model can show the hemodynamic characteristics of BCS , and its hemodynamic parameters could be used for clinical practice .It will facilitate the study on correlation of complex hemodynamic parameters and morphology changes of inferior vena cava vascular .
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Objective To investigate an effective algorithm for image segmentation in cervical cancer cell adhesion , which enables accurate segmentation of the contour of adherent cells .Methods The images of target cells were extracted from the background area using level set methods , normalized with minimum values of transformation algorithms ,and multi-plied by the gradient image points in the region of interest ( ROI) to inhibit the undesired gradient information before the im-ages of adherent cells were segmented using labeled watershed algorithm .Results and Conclusion Compared to conven-tional watershed segmentation methods , this algorithm is not only effective in image segmentation of adherent cervical cancer cells with uneven staining and more accurate segmentation lines established around the contours of adherent cells , but of high clinical value .