After PET images are reconstructed by OSEM, a spatial filter which exploits the correlation between neighboring voxels, is applied to remove noise. A new filtering method is proposed that also exploits the correlation between voxels from the same tissue. Anatomical priors are processed for bias correction and registered to PET images. For each voxel, similar voxels within the PET volume are identified using KNN method in the feature-space built by anatomical priors. These similar voxels and also the neighboring voxels are then used to remove the high frequency noise on PET images using a Gaussian and a weighted averaging filter.