Penalized maximum likelihood method for reducing limited-angle artifacts in image reconstructions for a dual-panel high-spatial-resolution pet system

Whole-body positron emission tomography (PET) system has limited spatial resolution for imaging human head and neck cancer (HNC) due to the small size of lymph nodes. We are developing a dual-panel high-spatial-resolution PET system for better imaging HNC. The PET system is designed as a dual-panel geometry to consider the patient’s comfort, but the limited angular coverage of the imaging plane leads to distortions in reconstructed images. In this work, we study a penalized maximum likelihood (PML) image reconstruction method for reducing the limited-angle artifacts arising from the insufficient angular sampling. A prior image is pre-reconstructed from a whole-body low-spatial-resolution PET scan. A PML image reconstruction is then performed with a regularization term that penalizes the dissimilarity between the prior image and the image to be reconstructed for the dual-panel PET scan. An update equation with guaranteed monotonic convergence is derived for the PML reconstruction where a resolution model is incorporated into the regularization term. We conduct computer simulations of PET scans of a cylindrical phantom with hot spheres to evaluate the performance of the PML reconstruction method. Our Results show that the deformation of the background and 6-mm and 8-mm diameter hot spheres in the PML reconstruction of the phantom is eliminated with the regularization strength γ being 0.02 or larger, while the deformation of 3-mm and 4-mm diameter spheres is not completely eliminated. The PML reconstruction with an appropriate γ achieves higher contrast recovery coefficient (CRC) of hot spheres than the prior image and can resolve small features like the 3-mm and 4-mm diameter hot spheres which are not resolvable in the prior image. The method proposed in this work makes the dual-panel high-spatial-resolution PET system promising for imaging HNC