Study On Volume Rendering And Visualization For Medical Images

Volume rendering (VR) is a hot subject of medical images processing. It is an important application of computer graphics and image processing in biomedical engineering. Since the VR technique is involved the subjects of computer graphics, digital image processing and some related medical knowledge, it is a multi-disciplinary topic. In recent years, the VR technique for medical images is widely used in diagnosis, surgery planning and simulating, plastic and artificial limb surgery, radiotherapy planning, and teaching in anatomy.In this thesis, some key issues of the VR technique are systematically investigated. Firstly, for the image filters and image interpolation between slices, a integrated interpolation algorithm is presented based on the contour shape and correspondence matching, which keeps the shapes and grays information the objects of interest. Secondly, the fidelity of effect of the VR for medical images is studied, and a continuous-gradient-based method for transparent volume rendering is proposed, which vivifies the results of volume rendering. For the direct volume rendering, this thesis presents an accelerated ray-casting volume rendering algorithm based on three-dimensional space coherence and an accelerated tri-linear interpolation algorithm based on classification, both of which ensure the real-time volume rendering. Thirdly, a new volume rendering method based on the 3D texture mapping hardware assisted accelerating is synthetically analyzed. Finally, all the algorithms and techniques are applied in the research and development of virtual scalpel. A tissue-based volume cutting technique is presented, which adds the characteristic of tissue on the basis of the traditional volume cutting technique and achieves free cutting oriented the object-tissue of interest. In addition, a reconstruction technique of the planar and curved section cut by virtual scalpel is also implemented. The experimental results with the real clinic image data demonstrate the effectiveness of the proposed algorithms and their applications.