Weighted Wiener Method in the Denoising of Diffusion Tensor Images

Diffusion weighted images are affected by several artifacts and noise which complicate the analysis and interpretation of diffusion tensor image. The method we present in this thesis works for the denoising of diffusion weighted images, which based on the theory of adaptive wiener method and takes into account the multi-boundary character of the diffusion weighted image. In this thesis we modified the adaptive wiener method to obtain more reliable filter result when it is performed on the multi-boundary DWI image. The method was illustrated by the synthetic and real data and the result has supported the filtering methodology proposed in this thesis.