Disclosed is a deep learning-based low dose PET 3D reconstruction method, which comprises: losslessly back-projecting low-dose PET original data onto an image domain; selecting an appropriate 3D deep neural network structure to fit a mapping between the low-dose PET back projection to a standard dose PET image; after performing learning on training samples and fixing a network parameter, PET image 3D reconstruction starting from low-dose PET original data is achieved, yielding low-dose PET reconstructed images having higher resolution and lower noise than those obtained through traditional reconstruction algorithms and image domain noise reduction.
DEEP LEARNING-BASED LOW DOSE PET 3D RECONSTRUCTION METHOD