Research On Visualization Technology Of Medical Image Data Based On Visual Optimization

At present,the visualization technology of medical image data is developing rapidly.The researchers showed the corresponding visualization images through the different drawing methods.However,during the acquisition,there are empty voxels and noises in the medical image data for various reasons,which tends to be easily displayed during the visualization process,so that the user is affected to a certain extent when operating the visualization image.To this end,this paper has conducted in-depth research on the problems existing in the visualization of medical image data.This paper first introduces the theory and related technologies of medical image data visualization,and further introduces the design principle of transfer function.On this basis,the optimization of the transfer function in 3D image is proposed.The 2D slice in different directions of 3D image is extracted by introducing the slice method,and the image enhancement is carried out by using three image enhancement methods.The method is verified by experiments.Effectiveness.The two visualization methods are combined to realize the related visualization system.The main contributions of this paper are as follows:(1)The transfer function in 3D image volume rendering plays an important role.Its selection and setting directly affect the visualization of medical image data.Aiming at the three-dimensional medical image rendering,by studying the design principle and design method of transfer function,a semi-automatic transfer function based on entropy theory is proposed to improve the global display of 3D medical image visualization and the optimal display of focus context.In this paper,the experimental comparison shows that the optimized 3D medical image has better improvement in the rendering time and rendering effect than the gradient opacity function.(2)For the display of two-dimensional slices,there are noise and empty voxel problems.In order to solve the image noise and preserve the details and edge information,a two-dimensional slice optimization method based on the total variation model is proposed by studying the image enhancement technology.Three image enhancement algorithms,such as histogram equalization,image fusion and total variational model,are used to solve the problems of edge loss,contrast blur and noise interference of two-dimensional medical images.The three methods were tested by the peak signal-to-noise ratio(SNR)and the average structural similarity of the image quality evaluation index.The validity of the total variation model in the enhancement of the two-dimensional slice image was compared.(3)Based on the above two methods,this paper develops a visually optimized medicalimage data visualization interactive system,which includes three-dimensional visualization and visual analysis functions for medical image data.The three-dimensional data visualization effect can be optimized and improved by adjusting the transfer function,and the two-dimensional slice is optimized by the image enhancement method to effectively optimize the application of the system.