A generalized diffusion based inter-iteration nonlinear bilateral filtering scheme for PET image reconstruction.
In this paper, a new inter-iteration filtering scheme based on diffusion Maximum a Posteriori (MAP) estimation for Positron emission tomography (PET) image reconstruction is proposed. This is achieved by gaining the insights into the classical MAP iteration (e.g. the 'one-step-late' algorithm, OSL) and the several well-established approximations to the diffusion process. We show that such a new technique allows additional insight and sufficient flexibility for further investigations on some nonlinear filters based reconstruction algorithms. In particular, we suggest the bilateral filter as a nice application in which image smoothing while edge preserving can be readily obtained by the combination of the range and domain filters. The feasibility and efficiency of the proposed method are verified in the substantiating experiments conducted on both the computer simulated and real clinical data.
Zhou
Jian
J
Laboratory of Image Science and Technology, Southeast University, China. zjseu@hotmail.com
Zhu
Hongqing
H
Shu
Huazhong
H
Luo
Limin
L
D000465:Algorithms; D001185:Artificial Intelligence; D001921:Brain / Q000000981:diagnostic imaging*; D016000:Cluster Analysis; D004058:Diffusion; D005240:Feasibility Studies; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity