A New Method for PET Image Reconstruction Using Fourier-Wavelet Moment

In this paper, a new non-regularization method for positron emission tomography (PET) reconstruction is proposed. The proposed method is a feature-based method using Fourier-Wavelet basis. In order to obtain the reconstructions, we have to calculate the Fourier-Wavelet moment (FWM) from the measurements. To achieve this, iterative method is employed. The rotation invariance property of the proposed basis permits us to reduce computational cost. A row-action (RA) like fast convergent algorithm is used to further accelerate the convergence rate. In experiment, we compare the proposed method with some existing algorithms. The results show that our method offers good reconstruction quality compared to conventional MAP method