Title :
Denoising DWI based on regularized filter
Author :
Zhang, X.F. ; Ye, H. ; Tian, W.F. ; Chen, W.F.
Author_Institution :
Shanghai Normal Univ., Shanghai
Abstract :
The Rician noise introduced into the diffusion weighted images (DWI) can bring serious impacts on tensor calculation and fiber tracking. To decrease the effects of the Rician noise, many anisotropic diffusion denoising methods have been presented. Among all these methods, the P&M filtering method is most popular. Although efficient in alleviating the effects of the noise, the classical P&M filter has shortcomings such as instability and ill-posedness. In this paper, a regularized anisotropic diffusion filter was presented and applied to restore the DWI. The presented filtering strategy displayed well posedness and good preservation of edges. To evaluate its efficiency in accounting for the Rician noise, the PSNR and MSSIM metrics were used for the first time. The results acquired from the synthetic and real data proved the better performance of the presented filters.
Keywords :
biomedical MRI; filtering theory; image denoising; image restoration; medical image processing; muscle; DWI restoration; MSSIM metrics; P&M filtering method; PSNR metrics; Rician noise effects; anisotropic diffusion denoising methods; denoising DWI; diffusion weighted images; edges preservation; fiber tracking; filtering strategy; regularized anisotropic diffusion filter; tensor calculation; Anisotropic magnetoresistance; Biomedical engineering; Diffusion tensor imaging; Filtering; Filters; Image restoration; Noise reduction; PSNR; Rician channels; Tensile stress;
Conference_Titel :
Bioengineering Conference, 2007. NEBC '07. IEEE 33rd Annual Northeast
Conference_Location :
Long Island, NY
Print_ISBN :
978-1-4244-1033-0
Electronic_ISBN :
978-1-4244-1033-0
DOI :
10.1109/NEBC.2007.4413308