Modified complex diffusion based nonlinear filter for restoration and enhancement of magnetic resonance images Online publication date: Mon, 13-Feb-2017
by R.B. Yadav; Subodh Srivastava; Rajeev Srivastava
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 23, No. 1, 2017
Abstract: In this paper, a new method is proposed for removal of Rician noise from MRI. Method is casted into a variational framework, consists of two terms wherein the first term is a data likelihood term and the second term is a prior function. The first term is obtained by minimising the negative log likelihood of Rician pdf. Owing to ill-posedness of the likelihood term, a prior function is introduced which is a nonlinear complex diffusion based filter. A regularisation parameter is used to balance the trade-off between data fidelity term and prior. The performance analysis of the proposed method with other standard methods is presented for Brain Web dataset. The values of performance measures such as PSNR, RMSE, SSIM, and CP are presented for various noise levels. From the simulation results, it is observed that the proposed method is performing better in comparison to other methods in consideration.
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