Gibbs Artifact Reduction by Nonnegativity Constraint

Abstract

This paper proposes a 2-step image reconstruction method in which the nonnegativity constraint in the iterative maximum-likelihood expectation maximization (MLEM) algorithm is used to effectively reduce Gibbs ringing artifacts. Gibbs artifacts are difficult to control during imaging reconstruction. The proposed method uses the postprocessing strategy to suppress Gibbs artifacts. In the first step, a raw image is reconstructed from projections without correction for point spread function (PSF). The attenuation correction can be performed in the first step by using, for example, the iterative MLEM or ordered-subsets expectation maximization (OS-EM) algorithm. The second step is a postprocessing procedure that corrects for the PSF blurring effect. If the target features (e.g., hot lesions) have a positive background, removing the background before application of the postprocessing filter significantly helps with target deblurring and Gibbs artifact suppression. This postprocessing filter is the image-domain MLEM algorithm. The background activity is attached back to the foreground after lesion sharpening. Computer simulations and PET phantom studies were performed using the proposed 2-step method. The background removal strategy significantly reduced Gibbs artifacts. Gibbs ringing artifacts generated during image reconstruction are difficult to avoid if compensation for the PSF of the system is needed. The strategy of separating image reconstruction from PSF compensation has been shown effective in removal of Gibbs ringing artifacts.