Research On Importance-based Composition For 3D Volume Visualization Of Medical Image

Medical image 3D visualization is an emerging technology which is developed on the basis of 2D imaging. With the developments of medical equipment, the emergence of a large number of high-resolution medical image data making how to better view and display the structural information of the tissue and organ has become a hot issue in the field of medical image 3D visualization. In the volume rendering, the introduction of non-photorealistic rendering can enhance the rendering area of interest and control of the draw result neatly which is the focus of research nowadays.In this paper, we focus on the research of 3D visualization of medical images, and exploit non-photorealistic rendering method to get rich rendering result. In which, we discuss how to design the voxel classification method and the non-photorealistic rendering by importance-based composition equation. In this dissertation, ray casting algorithm is analyzed. Taking OpenGL as graphic API, concrete implementation method of ray casting algorithm based on GPU is expounded in detail. In this paper, we propose importance-based composition which can control the rendering of the drawing process visibility. Apply the gray value interval classification function and the gradient region classification function of volume data basic feature information extraction. Further more, the paper also proposes the application of Frangi vascular filtering algorithm to extract the vascular structures, and exploit morphological filtering algorithm corresponding improvement. In order to facilitate user operation and render the results in a window, it also built a 3D visualization system capable of the proposed theoretical method better display.In this paper, we use a variety of data set for testing, including the 3D carotid ultrasound data, 3D cardiac CT data and so on. By comparing with the existing methods, we find that the method we proposed has obvious advantages, which can make a better visualization. Then we build a 3D medical image visualization system which has a friendly user interface, and it is convenient for doctors to operate.