A diffusion-matched principal component analysis (DM-PCA) based two-channel denoising procedure for high-resolution diffusion-weighted MRI - Fig 2

<p>Comparison of DWI denoising through filtering signals across nearest neighboring voxels and diffusion-matched voxels: The red dot in (a) shows a target voxel (displayed on top of mean DWI map), whose signals in 6-direction DWI scans are to be denoised. In many existing denoising methods, signals of nearest neighboring voxels in a patch (see b) are the input of a filtering procedure. In contrast, we identify a group of voxels that demonstrate very similar signal variation patterns along the diffusion dimension but are not necessarily neighboring (see c) for subsequent filtering procedures. Panels d, e and f show an input image, nearest-neighboring PCA produced image, and DM-PCA produced image, respectively. Residual maps obtained with nearest-neighboring PCA and DM-PCA methods are shown in panels g and h, respectively.