Computer-aided CT image processing and modeling method for tibia microstructure

We present a method for computed tomography (CT) image processing and modeling for tibia microstructure, achieved by using computer graphics and fractal theory. Given the large-scale image data of tibia species with DICOM standard for clinical applications, we take advantage of algorithms such as image binarization, hot pixel removing and close operation to obtain visually clear image for tibia microstructure. All of these images are based on 20 CT scanning images with 30 μm slice thickness and 30 μm interval and continuous changes in pores. For each pore, we determine its profile by using an improved algorithm for edge detection. Then, to calculate its three-dimensional fractal dimension, we measure the circumference perimeter and area of the pores of bone microstructure using a line fitting method based on the least squares. Subsequently, we put forward an algorithm for the pore profiles through ellipse fitting. The results show that the pores have significant fractal characteristics because of the good linear correlation between the perimeter and the area parameters in log–log scale coordinates system, and the ratio of the elliptical short axis to the long axis through ellipse fitting tends to 0.6501. Based on support vector machine and structural risk minimization principle, we put forward a mapping database theory of structure parameters among the pores of CT images and fractal dimension, Poisson’s ratios, porosity and equivalent aperture. On this basis, we put forward a new concept for 3D modeling called precision-measuring digital expressing to reconstruct tibia microstructure for human hard tissue.