Diffusion weighted image (DWI) is multi-boundary in nature, and it is particularly important to get accurate boundary signals of DWI . A new method combing bidimensional empirical mode decomposition (BEMD) with modified adaptive Wiener filter is proposed. Through BEMD method the degraded image is decomposed into a detail part and a residual part. The detail part of the image contains the boundary signal and the noise of the degraded image, and the residual part describes the image tendency. Thus, the DWI data is decomposed by BEMD method at first, and then, the modified adaptive Wiener filter is applied to remove the noise in the detail part of DWI and the residual part is thus handled. Finally, the denoised detail image and its residual are combined to form the denoised DWI. The method is performed on real DWI data. Experiment results positively show that the proposed method removes noise effectively and keeps the boundary of DWI successfully.