A Model-Based Denoising Adaptive Diffusion Method Based on Multi-Scale Bilateral Filter

摘要

In order to filter out the noise points of the medical spine model effectively and keep the details of the model better, a model-based denoising adaptive diffusion method based on multi-scale bilateral filter is proposed. This method firstly extracts the contour lines of the 3D model of the spine by using bilateral filter in multi-scale conditions, and then designs and improves the adaptive diffusion coefficient so as to optimize and control the whole diffusion process. Then, according to the discreteness of the image, the corresponding discrete iterative equations are established to discretize the iterative process, and the iteration stopping criterion is designed to make the denoising and smoothing image model stop the iteration when the correlation between that image model and the noise is the minimum, and finally to establish the spine image denoising model. After compared with the experimental results of the classical PM method, Catte method and other methods, this method achieves good filtering effect in denoising, and also preserves the edge detail features of medical image, much better than traditional filtering algorithm.