Segmentation And Hierarchical Visualization Of Medical Computed Tomography Arteriography Image

The development of medical image and computer graphics has brought great changes to medicine. Computed Tomography(CT), Magnetic Resonance Imaging(MRI), Ultrasonography(US), Positron Emission Tomography(PET) and other medical image techniques have been widely used in clinical medical diagnosis. Segmenting the regions of interest(ROI) from the medical image abtained by the imaging method above. 3D visualization can give doctors a accurate and clear view of 3D model based on visualization techniques, and it can assist the doctor to analyze and diagnose which greatly improves the diagnosis accuracy and scientificalness.Segmentation is the key step in medical image processing, which can directly affect the scientific nature and rationality of the 3D visualization and simulation of computational fluid dynamics. The main contents of this paper are as follows:(1) Counting the gray level distribution of the image. The interest area can be displayed by modifying the transfer function. 3D data can be smoothed by the curvature flow filter. The similarity function is introduced into the traditional confidence-connected method. A novel algorithm is proposed to sequentially segment the 3D data based on the improved confidence-connected method, and it can strip the important tissues.(2) The method based on ISODATA clustering and region growing is proposed to sequentially segment the bone, removing the bones of the shade. Use this method to sequentially extract coronary artery.(3) 3D visualization are respectively applied to the source data, the 3D segmentation data, the boneless data, and the coronary artery. And then plotting the extracted spine and coronary artery in the same visualization window to complete the purpose of hierarchical visualization.This paper realized the hierarchical visualization of the human chest skin, muscle, bone, heart and blood vessels. Each structure can be displayed independently, arbitrary rotation, zoom in and out. This paper basically completed the purpose of hierarchical visualization, and it provided a clear and intuitive 3D model for the doctor.