A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram
We propose filtering the PET sinograms with a constraint curvature motion diffusion. The edge-stopping function is computed in terms of edge probability under the assumption of contamination by Poisson noise. We show that the Chi-square is the appropriate prior for finding the edge probability in t...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2013/732178 |
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| _version_ | 1832545302175809536 |
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| author | Musa Alrefaya Hichem Sahli |
| author_facet | Musa Alrefaya Hichem Sahli |
| author_sort | Musa Alrefaya |
| collection | DOAJ |
| description | We propose filtering the PET sinograms with a constraint curvature motion diffusion. The edge-stopping function is computed in terms of edge probability under the assumption of contamination by Poisson noise. We show that the Chi-square is the appropriate prior for finding the edge probability in the sinogram noise-free gradient. Since the sinogram noise is uncorrelated and follows a Poisson distribution, we then propose an adaptive probabilistic diffusivity function where the edge probability is computed at each pixel. The filter is applied on the 2D sinogram prereconstruction. The PET images are reconstructed using the Ordered Subset Expectation Maximization (OSEM). We demonstrate through simulations with images contaminated by Poisson noise that the performance of the proposed method substantially surpasses that of recently published methods, both visually and in terms of statistical measures. |
| format | Article |
| id | doaj-art-48f82ea2a5d04151b142ac662c3d83f8 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-48f82ea2a5d04151b142ac662c3d83f82025-02-03T07:26:07ZengWileyJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/732178732178A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data SinogramMusa Alrefaya0Hichem Sahli1Department of Electronics and Informatics (ETRO-IRIS), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, BelgiumDepartment of Electronics and Informatics (ETRO-IRIS), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, BelgiumWe propose filtering the PET sinograms with a constraint curvature motion diffusion. The edge-stopping function is computed in terms of edge probability under the assumption of contamination by Poisson noise. We show that the Chi-square is the appropriate prior for finding the edge probability in the sinogram noise-free gradient. Since the sinogram noise is uncorrelated and follows a Poisson distribution, we then propose an adaptive probabilistic diffusivity function where the edge probability is computed at each pixel. The filter is applied on the 2D sinogram prereconstruction. The PET images are reconstructed using the Ordered Subset Expectation Maximization (OSEM). We demonstrate through simulations with images contaminated by Poisson noise that the performance of the proposed method substantially surpasses that of recently published methods, both visually and in terms of statistical measures.http://dx.doi.org/10.1155/2013/732178 |
| spellingShingle | Musa Alrefaya Hichem Sahli A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram Journal of Applied Mathematics |
| title | A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram |
| title_full | A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram |
| title_fullStr | A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram |
| title_full_unstemmed | A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram |
| title_short | A Novel Adaptive Probabilistic Nonlinear Denoising Approach for Enhancing PET Data Sinogram |
| title_sort | novel adaptive probabilistic nonlinear denoising approach for enhancing pet data sinogram |
| url | http://dx.doi.org/10.1155/2013/732178 |
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