Study On Segmentation And Visualization Of Teeth From Dental CT Reconstruction Image

Nowadays, as the developments of all kinds of the biomedical technology, the technology spawned a variety of computer aided diagnosis system and computer aided system for different purposes of research become a hot topic in the field. Low-dose Dental CT is the computer aided diagnostic system designed for health checks and disease diagnosis and treatment of dental and oral and maxillofacial, and in the process of dental CT image segmentation and 3-D visualization technology is the key technologies of the inspection and diagnosis and treatment of diseases.Medical image segmentation is always a traditional and challenging project, and it is the basis of computer-aided analysis, medical image visualization and disease diagnosis. Medical image segmentation contains two item questions. One is the given tissue recognition of body region from medical image, and the other is method of description and extraction of object region. In most occasions, medical image segmentation is more difficult than other image segmentation, because of the diversity and complexity of the medical imaging techniques. Learn the important thoughts of some of the fluid, Osher and Sethian first proposed Level-set algorithm, which is an effective solution to the problem of curve evolution of numerical methods and computational stability, suitable for the space of any dimension. Level-set method coupled with curve evolution theory conquers many limitations of general active contours model, which widens the utilization of active contours model. This dissertation analyses the Level-set method based on the Chan-Vese model, by the research of the traditional Level-set method and the do not need to initialize Level-set method. Level-set method is applied to reconstruct image of the dental CT and extract the target area (teeth) step by step and prepare for subsequent image visualization.Visualization technology of medical images is an important application of computer graphics and image processing in biomedicine engineering. The technology can appear the body’s tissues and lesions in the shape of three-dimensional for the doctor’s diagnosis and treatment. Doctor can lossless get a lot of information of the body’s internal anatomical structures, access to the relative spatial relationships of the various tissues and organs, which greatly promoted the development of medicine. This paper studies the basic principles of the Marching Cubes algorithm (MC) and applies to the reconstruction of teeth three-dimensional structure based on dental CT. Marching Cubes algorithm (MC) proposes a method for searching cells and extracting isosurface, nowadays the most widely used 3-D reconstruction algorithm. According to the corresponding structure of the teeth, the Marching Cubes algorithm is properly adjusted and we can get good effect of tooth body’s 3-D structure.