Computer Aided Diagnosis System For Orthopedic Diseases Based On The Key Technology Of Medical Image Processing

There are a variety of orthopedic diseases with a complex professional background,and it is very prone for missed diagnosis and misdiagnosis to occur.The computer-aided diagnosis system for orthopedic diseases based on the key technology of medical image processing locate and display the lesion location area,measure and provide disease diagnosis indicators with two-dimensional and three-dimensional visualization methods,and assist orthopedic surgeons in diagnosis from the comprehensive perspective of visual visualization and quantitative indicators,which is of great significance for improving the rate and accuracy of diagnosis of orthopedic diseases,reducing the pain of patients and shortening the treatment time of diseases.The diagnosis method for orthopedic diseases relies on medical images.Traditionally,doctors find out the abnormal lesions and reconstructed the position with two-dimensional medical images,size and shape in the brain.This diagnosis method lacks quantitative indicators and does not make use of three-dimensional visual information,so it is very prone to misdiagnose and miss diagnosis in the diagnosis for complicated and non-obvious orthopedic diseases.In order to solve this problem,this paper designed and developed a computer aided diagnosis system of orthopedic diseases based on the key technology of medical image processing,which introduced quantitative index information and two-dimensional and three-dimensional visualization visual information for doctors to diagnose orthopedic diseases.In this paper,the common orthopedic diseases gout and cartilage defect were taken as the research objects,and the key technologies,such as medical image segmentation algorithm,medical image registration algorithm and medical image visualization algorithm involved in the computer-aided diagnosis for gout and cartilage defect were studied.The main research contents of this paper are as follows:1)To solve the problem that it is difficult to separate and extract the region of interest from orthopedic medical images by a single method,the combined segmentation method of medical images was studied.A cartilage segmentation algorithm based on edge,threshold and morphological operation was proposed to create conditions for subsequent registration and fusion of cartilage.An algorithm was proposed to segment the crystal region of bone and urate.The method of threshold segmentation,regional growth and logistic regression was used to solve the problem of the difficulty in distinguishing the crystal region of bone and urate.In order to improve the accuracy of gout diagnosis,a urate crystal artifact removal algorithm based on 3D body segmentation and region labeling was introduced.2)To solve the problem that medical images for orthopedic diseases may have inconsistent spatial positions,an image registration method based on volume feature point selection and Powell was proposed.The optimal spatial transformation parameters were found by combining the linear search strategy of the golden section method with the optimization of Powell algorithm,which maximized the normalized mutual information between the images to be registered,thus ensuring the consistent position in the two-dimensional space.The volume feature points are selected in an interactive manner,and their screen coordinates are mapped to three-dimensional data field space coordinates.The Euclidian distance between the volume feature points on the transformed template of intact cartilage in the digitized bone bank and the corresponding volume feature points on the image of the cartilage to be diagnosed was taken as the objective function.Singular value decomposition is used to calculate the spatial transformation parameters of the floating image with the minimum objective function,so as to align the spatial positions of the pixels in the image sequence of the cartilage to be diagnosed with the intact cartilage template sequence.3)In order to provide sufficient information to assist orthopedic doctors in disease diagnosis,a new method for diagnosis and evaluation of orthopedic diseases based on visualization technology and quantitative index calculation was proposed.3D visualization can be realized by improving MC 3D reconstruction algorithm,and multiple objects can be reconstructed at the same time.In addition,rapid prototyping technology can also be used to realize the visual evaluation of 3D model entities.A method of gout auxiliary diagnosis and evaluation based on quantitative index and three-dimensional visualization was designed.The total volume of urate crystal could be obtained by quantitative index calculation,and the position and shape of bone and urate crystal could be provided by three-dimensional visualization to assist doctors in gout diagnosis.A method for auxiliary diagnosis and evaluation of cartilage defect based on 2D and 3D visualization was designed.The visualization method was used to display cartilage defect area containing internal structure,3D model image and 3D printed solid 3D model to assist doctors in diagnosis.4)In order to realize the function of auxiliary diagnosis for orthopedic diseases and verify its effectiveness,this paper independently developed and designed a computer aided diagnosis system for orthopedic diseases.The system consists of five modules,which can input and output medical image information,algorithm processing,effect display and other functions.The system can be used to assist the diagnosis for gout and cartilage defects,and it can also be modified and extended to assist the diagnosis for other orthopedic diseases.The experimental results show that the segmentation algorithm for cartilage tissue,the segmentation algorithm for bone and urate crystal,the algorithm for urate crystal artifact removal,the two-dimensional and three-dimensional image registration algorithm and the visualization algorithm are effective.The system developed in this paper can be applied to the auxiliary diagnosis and assessment for gout and cartilage defects in clinic,providing sufficient basis to assist doctors in diagnosis.