DTI Image Denoising Based on Complex Shearlet Domain and Complex Diffusion Anisotropic Filtering

Diffusion tensor imaging (DTI) is an imaging modality that has developed in recent years. It is a non-invasive technique and needn’t contrast medium. However, the SNR of DTI data is relatively low and clinically polluted by noise, which can bring serious impacts on tensor calculating, fiber tracking and other post-processing. In order to reduce the influence of noise on DTI images and improve the efficiency of diffusion tensor imaging effectively, a new DTI denoising scheme is proposed by combining the complex Shearlet transform and complex diffusion anisotropic filtering. The experiment results acquired from the simulated and real data prove the good performance of the presented algorithm.