Research And Application Of 3D Visualization Method Of Brain Medical Images

In recent years,the prevalence of the brain diseases has continued to rise,and the trend of younger age is obvious.The prevention and treatment of the brain’s diseases has become one of the current major social problems.In general,the surgery is the main method to treat the brain diseases.With the help of CT or MRI images,more information about the disease can be got to increase the success rate of operation.The 3D visualization technology of medical images is to perform 3D reconstruction of the CT or MRI image sequence of the human organ structure and tissue function.The detailed information in the volume data can be dispalyed on the screen to assist doctors to observe multi-dimensionally th diseased organs or tissues for,etiological analysis.Further more objective and accurate diagnosis and treatment plans can be formulated.Therefore,the 3D visualization technology of medical images has a certain realistic significance,the scientific value and application prospect in the diagnosis and treatment,the scientific research and the teaching activities of the brain diseases.Volume rendering is one of the main technologies for the 3D visualization of medical images,which aims at efficient classification of volume data.A better transfer function is designed,which endows all voxels with different colors and opacity and renders them on the screen.Among them,transfer function design and volume rendering are the key techniques of volume rendering,which directly affect the visual effect.Therefore,this thesis focuses on volume rendering and transfer function design in the 3D visualization of the brain medical images.1.A transfer function design method based on shape features is proposed.Based on morphological features,feature extraction,watershed segmentation and K-means algorithm are used to design the transfer function.To be specific,the watershed algorithm can aggregate voxels with similar features and maintain the basic features,so as to effectively reduce the data scale.The mean algorithm can perform real-time clustering tasks,guide the users to perceive the results of parameter adjustment in a short time,so as to complete the lock-in of the region of interest.This method has been implemented in the 3D medical image visualization system and achieved satisfactory results.2.A 3D medical image visualization system is designed.The parameters required for volume rendering are weighted by voxel brightness and shape eigenvalues.For uniformly distributed data sets,linear weights are used,while exponential weights are used for data sets with sharp changes in brightness.The system has the basic operation function of 3D visualization of medical images,to realize volume rendering,which meets the needs of the project.3.A fast image rotation algorithm based on Bresenham algorithm is proposed.In practical applications,when users rotate 3d medical images,the next frame will appear before the previous frame disappears,resulting in image tearing on the screen.In order to solve this problem,the rotation speed of 2d medical image is optimized first.The two adjacent edges of the rotated rectangle are represented by Bresenham scan lines.By setting one edge as the support edge and the other as the moving edge,the moving edge slides along the support edge to sweep out the rotated rectangle.This method can quantitatively explain the causes of holes in the forward operation of image rotation,which is conducive to the establishment of a fast rotation algorithm.