Effective Anatomical Priors for Emission Tomographic Reconstruction
Bayesian tomographic reconstruction with anatomical side information from other imaging modalities can improve both image quality and quantitation in emission tomography for both single-photon emission computed tomography and positron emission tomography. However, the complexity and sensitivity to registration error between function and anatomical images often limit its clinical applications. To alleviate these challenges, this study proposes two priors, anatomical median root prior (AMRP) and anatomical mean prior (AMP), with a simple scheme of incorporating anatomical information. The priors are based on a simple edge-preserving prior that aims to retain the true intensity edges without blurring, median root prior (MRP), by replacing the median value among neighboring pixels with the median or mean value in a corresponding predefined anatomical region. Digital simulations and Monte Carlo simulations were conducted to evaluate the performance of the proposed methods. As compared to MRP, the proposed priors both showed sharper edges, better uniformity, and more accurate activity recovery with well-aligned anatomical and functional images. In addition, a tolerance study in terms of the misregistration between anatomical and functional images was also performed. Acceptable results were obtained for both priors when misalignment was less than 2 pixels, which can be easily achieved in real applications. The proposed anatomical priors for emission tomographic reconstruction can improve both visual and quantitative performance, and are not sensitive to misregistration errors between anatomical and functional images.