Convergent Bayesian Reconstruction for PET Using New MRF Quadratic Membrane-Plate Hybrid Multi-order Prior
The effectiveness of Bayesian reconstruction, or maximum a posteriori (MAP) method, has been proved in positron emission tomography. In this article, a novel convex MRF (Markov random fields) Membrane-Plate hybrid prior for Bayesian reconstruction, which combines quadratic smoothness prior of different orders, is proposed. The design of the new prior is based on the intrinsic properties of the two smoothness prior of different orders and aims to make an adaptive use of the two smoothness priors. The convexity of the new prior energy functional is ensured. Simulation experiments of their application in PET (Positron Emission Tomography) reconstruction are illustrated. Visional and quantitative comparisons showed the new hybrid prior’ good performance in lowering noise effect and preserving edges.
KeywordsBayesian reconstruction MRF (Markov random fields) PET (Positron Emission Tomography) Membrane-Plate hybrid prior
Unable to display preview. Download preview PDF.
- 7.Lee, S.J., Rangarajan, A., Gindi, G.: Bayesian Image Reconstruction in SPECT Using Higher Order Mechanical Models as Prior. IEEE Trans. on Medical Imaging MI-14(4), 669–680 (1995)Google Scholar
- 9.Fessler, J.A., Erdoğan, H.: A paraboloidal surrogates algorithm for convergent penalized-likelihood emission reconstruction. In: Proc. IEEE Nuc. Sci. Symp. Med. Im. Conf., vol. 2, pp. 1132–1135 (1998)Google Scholar