An encoder-decoder network for direct image reconstruction on sinograms of a long axial field of view PET.

Ruiyao MaJiaxi HuHasan SariSong XueClemens MingelsMarco ViscioneVenkata Sai Sundar KandarpaWei Bo LiDimitris VisvikisRui QiuAxel RomingerJunli LiKuangyu Shi
Published in: European journal of nuclear medicine and molecular imaging (2022)
The results demonstrate the feasibility of using deep learning to reconstruct images with acceptable image quality and short reconstruction time. It is shown that the proposed method can improve the quality of deep learning-based reconstructed images without additional CT images for attenuation and scattering corrections. This study demonstrated the feasibility of deep learning to rapidly reconstruct images without additional CT images for complex corrections from actual clinical measurements on LAFOV PET. Despite improving the current development, AI-based reconstruction does not work appropriately for untrained scenarios due to limited extrapolation capability and cannot completely replace conventional reconstruction currently.