Measurement Data Correction for Emission Tomography

In the problems of statistical reconstruction of emission tomography images, Bayesian reconstruction, or maximum a posteriori (MAP) method, has proved its superiority over others among all the regularization methods. To further improve the reconstruction, this paper presents a novel statistical image reconstruction method based on coupled feedback (CF) iterative model for emission tomography. This CF iterative algorithm updates the noisy emission sinogram (the measurement data of the detectors) using the latest reconstructed image. The experiments and the performance analysis confirm the virtue of the new method.