Research On The Visualization Technology And Geometry Measurement Of Three Dimensional Medical Image

Visualization in scientific computing (VISC) is the technology which can transform some data into the graphics or images displayed on the screen and perform the interaction processing by using the technology of computer graphics and image processing. Medical image visualization techniques play an important role in medical image processing and analysis, and it is one of the most successful applications of visualization in scientific computing. Rapid advances in the field of medical image visualization techniques are revolutionizing medicine. Computed tomography (CT), magnetic resonance imaging (MRI), ultrasonography (US) and other imaging modalities have been widely used in clinical diagnosis and therapy. With the aids of computers, extracting regions of interest (ROI) from CT, MRI, US and displaying them through 3D visualization techniques can help the physician observe the pathological regions more directly and more clearly, which will contribute to improving the accuracy of diagnosis. There are many visualization techniques, such as volume rendering, surface rendering and local displaying. How to make full use of these visualization techniques to help the physician get the most valuable information has become a hot issue in visualization research.The study target of this subject is "segmentation and visualization of three dimensional breast glandular ducts and masses". We study at the segmentation and visualization techniques of medical image and deal with the graph using the wavelet and mathematical morphology. We introduce the computer graphics, the wavelet analysis, the mathematical morphology and their application in our image processing. And then we segment and visualize the three dimensional glandular ducts and masses therein through the use the software Amira 3.1. The segmented components are presented with triangular surface grids and tetrahedral volumetric tessellations, which can be colored (labeled) and embedded in situ in the original breast volume through the use of transparent display mode for better visualization. In conclusion, the breast volume segmentation and visualization serve as a great helper to radiologist for breast tissue analysis and cancer diagnosis by offering intuitive visualization and digital representations.