Abstract:

BACKGROUND: Traditional cancellous bone porosity detection methods such as direct method, gas expansion method, mercury injection method, density and osmotic suction measurement have many disadvantages, such as low efficiency, labor-intensive and complexity.
OBJECTIVE: To process cancellous bone chips using MATLAB image processing method to calculate cancellous bone porosity.
METHODS: Using MATLAB image processing method, the stained cancellous bone images were subjected to uneven lighting removal, image enhancement, binarization, removing interference objectives to obtain binary two-dimensional matrix.
RESULTS AND CONCLUSION: Slice image was composed of bone and pore space. The slice image was segmented to calculate its porosity. This solves the problem of the inequality of light intensity and other interferences in image information that affect the statistics. The image processing and analysis methods of bone slices were performed using MATLAB, which can be used for cancellous bone porosity measurements and be used to explore the distribution and variation of porosity. Selecting different regions to calculate the different porosity of each area can be used to analyze the distribution of the pore. This method provides a method for the study of trabecular bone structure.