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| Diffusion Weighted MRI Rician Noise Restoration Using Modified Wiener Filtering |
1 Department of Electronic Engineering, Chengdu University of Information Technology, Chengdu 610225, China
2 College of Computer Science, Sichuan University, Chengdu 610065, China
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Abstract According to Rician noise distribution from diffusion weighted magnetic resonance image and the bias from the traditional Wiener filter which is designed for Gaussian model, this paper encapsulated multi diffusion weighted magnetic resonance images from nearby directions for Wiener filtering. In the procedure, Wiener filter was modified for Rician noise model, and the parameters of filter were estimated through anisotropic area for further improvement of restoration. The simulation and experiment of both synthetic and in vivo diffusion weighted magnetic resonance image data demonstrated that the proposed method can effectively remove the noise in the diffusion weighted magnetic resonance image, and improve the quality and orientation information of diffusion tensor MRI. In 10% Rician noise condition, peak signal noise ratio of diffusion weighted magnetic resonance image was increased 10 dB, and mean angular variation of diffusion tensor MRI decreased 5 degree, which ensures better accuracy and robustness of the further applications.
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