High quality ordered subset expectation maximization reconstruction algorithm based on multi-resolution for PET images

Abstract

In Positron Emission Tomography(PET) imaging,Maximum Likelihood Expectation Maximization(MLEM) algorithm cannot be directly applied to clinical diagnosis due to suppressing noise ineffectively and converging slowly.Although Ordered Subset Expectation Maximization(OSEM) algorithm converges fast,it will lead to a significant decline in the quality of the reconstructed image.To address this problem,multi-resolution technology was introduced into the subset of the OSEM reconstruction algorithm to suppress noise and stabilize solving process.The experimental results indicate that the new algorithm overcomes the drawback of the traditional algorithm on degrading the reconstructed image and has the advantage of fast convergence.The proposed reconstruction algorithm can obtain a higher Signal-to-Noise Ratio(SNR) and a superior visual effect.