Image Processing And Image Analysis Of Biomaterial Degradation

Currently,with an excellent biologic compatibility and degradability, β-TCP bioceramic has been widely applied to solve bone deformation problem caused by pathological changes. And the degradation process of this kind of materials being imported into body has become a hot research topic. Therefore, it will play an important role in designing new type of degradable biomaterials to set a proper mathematic model which can simulate the degradation process of biomaterials imported into body. Since the images of the materials transplanted into organism in different periods hold rich information about materials change, they are to be analyzed and processed to extract the changed information and explore parameters for the simulation model.After several image processing theories and methods were researched, and the characteristics of the organism images were analyzed, texture feature K-mean value clustering method mainly based on wavelet transformation was chose to segment the images with a good segmentation effect. Wavelet transformation has a good time-frequency localizing characteristics. Image segmentation is an important step from image processing to image analysis. Different sections of image have different textures, and different laws features obtained from wavelet transformation form a feature space. The points in the feature space are clustered to form different regions according to K-mean value clustering method, and then the regions are mapped to original image space to get the result of image segmentation. In final, segmented images were analyzed, and the areas of all different sections of the image were calculated (presented with pixel number).The realization of image processing and image analysis was based on mixed programming between MATALB and VC++ which both keeps the advantages of MATLAB and holds a high executing efficiency of VC++. Thusit brings convenience for image analysis software development. In this paper, an analysis system for organism image was set up based on the mixed programming and it will be benefit to image analysis.