PET Sinogram Denoising by Block-Matching and 3D Filtering

We consider the denoising of noisy positron emission tomography (PET) sinograms by sparse 3D transform domain collaborative filtering. The filtering operation is realized by block-matching and 3D (BM3D) filtering algorithm that groups similar 2D sinogram fragments into 3D groups and filters each group by collaborative filtering. This filtering jointly filters the similar blocks in the transform domain and offers a way for efficient denoising while preserving essential information of each sinogram fragment. The obtained results are compared with conventional radial filtering and stackgram filtering that utilizes an intermediate stage between sinogram and image domains, called stackgram domain. Both quantitative and qualitative comparisons show that the proposed approach to filter the sinogram with BM3D filter outperforms the other filtering methods.