Study On Three-dimensional Imaging Aided Diagnosis System Of Brain Tumor

As a brain disease,brain tumors can cause serious harm to the health of patients.Conventional brain examinations commonly use MRI,CT and other fluoroscopic scans for image information extraction,but often only show in the two-dimensional level,the three-dimensional structure of the tumor and the specific position and shape in its brain need to rely on the doctor’s experience and imagination.The three-dimensional model of the brain tumor reconstructed by using three-dimensional visualization technology can display its own size and specific characteristics from multiple angles,intuitively display its own position,and facilitate doctors to observe the condition and plan the surgical path.Therefore,with the advancement of medicine and people’s increasing attention to their own health,the research of medical three-dimensional image-assisted diagnosis system for brain tumors has gradually become a hot research field.Based on VTK,Qt and other class libraries and BRATS2013 medical image dataset,this paper carries out the research work of medical three-dimensional image-assisted diagnosis system for brain tumors.The main goal is to meet the daily work needs of doctors and improve the diagnostic efficiency of doctors,and the research content and results of the paper are as follows:(1)The overall framework of the three-dimensional image-assisted diagnosis system of brain tumor medicine is designed,various functional modules of the system are designed,and the UI interface of the system is designed on the principles of simplicity,beauty,easy operation and easy to use.(2)An adaptive histogram equalization algorithm based on particle swarm optimization is designed to visually enhance brain medical images.Through the particle swarm algorithm,the information entropy of the image is used as the evaluation function,and the window area of the adaptive histogram equalization algorithm is used as the particle,and the window area of the image information entropy is calculated.The paper conducts a comparative experiment on the algorithm.The experimental results are objectively evaluated,and the experimental results prove that the algorithm can effectively enhance the image quality.(3)An improved adaptive threshold segmentation algorithm is proposed for brain tumor segmentation.After enhancing the image by power transformation and mean filtering,the image is initially segmented using the adaptive threshold segmentation algorithm based on the histogram,and then the largest region is found to use its central position as the seed point of the regional growth algorithm,and then the original image is secondarily segmented,which solves the problem of excessive segmentation.The paper conducts a comparative experiment on the algorithm,and the results of the comparison experiment show that the segmentation algorithm in this paper effectively improves the accuracy of tumor segmentation.(4)Different 3D mapping algorithms were used to reconstruct the sequence images of the segmented tumor and brain tissue in three dimensions,and then the three-dimensional models of brain tumors and brain tissues were fused to enhance the distinction between brain tumors and brain tissues in the model.The model comparison experiment was carried out to find the best three-dimensional fusion drawing method.(5)With the support of the VTK open source library,a number of auxiliary diagnostic function modules have been written,including:the segmentation module of the three-dimensional model to help doctors observe the internal results of the model,the body drawing transmission function adjustment function module to adjust the display effect of the three-dimensional model,the extraction of the three-dimensional model slice allows the doctor to observe the brain slice from three directions,the length and angle measurement function module helps the doctor to make better qualitative diagnosis,and the manual segmentation tumor module is designed to assist the brain tumor segmentation function to help doctors diagnose more flexibly.The three-dimensional image-assisted diagnosis system of brain tumor designed in this paper can effectively enhance the image quality,accurately segment the tumor and measure the tumor data,enhance the distinguishing effect between brain tissue and brain tumor in the three-dimensional model,improve the auxiliary diagnosis function of the system,and promote the development of the three-dimensional image-assisted diagnosis system of brain tumor medicine.