Medical Image Segmentation And Reconstruction Of Mesh Simplification

Medical image processing and analysis is the one of popular research projects, which is the project including much different knowledge and is the application of computer graphics and image process in the biomedical engineering. It covers many subjects such as computer graphics, image process and medical knowledge, and it is mainly constituted by the pre-processing of medical image, the segmentation of the apparatus and the tissue, visualization of 3D medical models, simplification of complex models, dividing cubes of models and so on.The primly contents of this thesis are pre-processing of medical image, image segmentation and the simplification of complex models. After studying and summing up many dissertations which obtained from the domestic and overseas scholars, we propose several new arithmetic, to improve the shortages of the classical's.The key work and innovations of this thesis mainly include:1. Research of the actuality of the pre-processing of medical image, image process and the simplification of complex models.2. Proposed a improvement of anisotropy filter in pre-processing of medical image, which not only wipes off the noise, but also keeps the high-frequency edge information, and improves the time-consuming shortage. Experiments show its advantage.3. Presented a new approach of skull's MRI segmentation based on decision making tree. Combining the pattern recognize and the distributing rule of tissue in the skull, it can auto-adapting segment the objects. Experiments show it is feasible and effective.4. Presented a improvement approach in medical image mutual segmentation. It improves the live wire arithmetic through using Fractional Differential to replace the integral grads, then segments the medical image series automatically by contour interpolation. Experiments show its advantages.5. Proposed a improvement of vertex deletion in medical model simplification. It defines a new measurement of vertex essentiality, to advance the quality of simplified models; and uses the advantage of auto-adapt octree to quicken up the speed of the model simplification. Experiments show its advantages.