Maximum-likelihood estimation of emission and attenuation images in 3D PET from multiple energy window measurements

This study explores the feasibility of incorporating energy information into a maximum-likelihood reconstruction of activity and attenuation (MLAA) framework. The attenuation and activity distributions were reconstructed from multiple energy window data, and a scatter function was added to the system model of the algorithm. The proposed energy-based method (MLAA-EB) was evaluated with simulated 3D phantom data, using the geometry and characteristics of a Siemens mMR PET-MR scanner. Results showed that the proposed algorithm is able to compensate for errors in the activity image caused by the incorrect assignment of attenuation values to the segmented MR. This is effective for small objects only, for large objects further solutions need to be found.