Research On Hip Joint Medical Image Segmentation And Registration Technology

As engineering and medicine continue to integrate and develop,the intersection of medicine and industry is now an important area of research and application.Among them,computer-aided technology is playing an increasingly important role in clinical diagnosis and treatment.This thesis focuses on the application of segmentation and alignment techniques in the field of computer graphics and vision to the clinical diagnosis and treatment of the hip joint,using automatic segmentation techniques to automatically extract the region of interest in the hip joint,which can help doctors to further diagnose and analyse the lesion,such as quantitative analysis and 3D visualisation.Through the study of the hip joint virtual and real image alignment technology,an AR visualisation-based image guidance system is provided to help doctors to determine the spatial location of the lesion more intuitively.The main research of this thesis is as follows.（1）In order to achieve automatic segmentation of the hip joint in CT images,an automatic segmentation algorithm based on the graph cut model is proposed.Firstly,an enhancement filter based on gradient and histogram is proposed to enhance the bone boundary information for the weak edges and narrow adjacent bone gaps that exist in the CT images of the hip joint.Through the output characteristics of the enhancement filter and the bone CT intensity range,the graph cut model was optimized and improved,the directed edge edge term and the a priori constrained region term were constructed,and the morphological properties were used for post-processing operations to finally realize the automatic segmentation of the hip joint.The experiments prove that the algorithm model proposed in this thesis has higher accuracy in the automatic segmentation of the hip joint compared with other algorithms.（2）To address the problem of how to achieve rapid quantification of the volume of femoral head necrosis lesions in clinical treatment of the hip joint.In this thesis,a Geodesic ACs segmentation model based on local area information is proposed.In this algorithm model,the advantageous features of the LRAC model and the Geodesic ACs model are fused to construct an active contour based on local area information for the blurred lesion edges and texture heterogeneity of the internal regions of the lesion in the femoral head necrosis region in CT images.model.The volume quantification of the segmented extracted lesion area is performed by the algorithmic model proposed in this thesis,so as to obtain the osteonecrosis volume,whose volume quantification error is in line with the clinical diagnosis range.It is demonstrated that the segmentation model proposed in this thesis is more accurate and reliable than other algorithms in the segmentation of femoral head necrosis regions.（3）To address the issue of image guidance in hip arthroplasty,this thesis proposes an image guidance system based on AR visualisation through the study of image alignment techniques.Firstly,a three-dimensional visualisation model of the extracted hip joint and its lesion area was carried out to obtain the virtual three-dimensional model required for image registration.In the image guidance process,the virtual 3D model of the femoral head with the lesion is registered to the corresponding position in the real space in real time by using the point-to-point registration method and the spatial conversion relationship established in this thesis to provide the doctor with intuitive real-time spatial information of the lesion in clinical treatment.The experimental results show that the image registration technique proposed in this thesis has good accuracy and reliability.