An emission imaging data reconstruction device comprising: an electronic processor; and a non-transitory storage medium storing instructions readable and executable by the electronic processor to perform an image reconstruction and enhancement process including: reconstructing emission imaging data to generate a low dose reconstructed image; applying a standardized uptake value conversion to convert the low dose reconstructed image to a low dose SUV image; and applying a neural network (46, 48) to the low dose SUV image to generate an estimated full dose SUV image; wherein the neural network (46, 48) is trained on a set of training low dose SUV images and corresponding training full dose SUV images to transform the training low dose SUV images to match the corresponding training full dose SUV images; wherein each training full dose SUV image and a corresponding one or more training low dose SUV images are generated by operations including: reconstructing an emission imaging data set to generate a training full dose image and applying the SUV conversion to the training full dose image to generate the training full dose SUV image; generating one or more training low dose emission imaging data sets by sampling the emission imaging data set; reconstructing each training low dose emission imaging data set to generate a training low dose image and applying the SUV conversion to the training low dose image to generate the training low dose SUV image. an electronic processor; and a non-transitory storage medium storing instructions readable and executable by the electronic processor to perform an image reconstruction and enhancement process including: reconstructing emission imaging data to generate a low dose reconstructed image; applying a standardized uptake value conversion to convert the low dose reconstructed image to a low dose SUV image; and applying a neural network (46, 48) to the low dose SUV image to generate an estimated full dose SUV image; reconstructing emission imaging data to generate a low dose reconstructed image; applying a standardized uptake value conversion to convert the low dose reconstructed image to a low dose SUV image; and applying a neural network (46, 48) to the low dose SUV image to generate an estimated full dose SUV image; wherein the neural network (46, 48) is trained on a set of training low dose SUV images and corresponding training full dose SUV images to transform the training low dose SUV images to match the corresponding training full dose SUV images; wherein each training full dose SUV image and a corresponding one or more training low dose SUV images are generated by operations including: reconstructing an emission imaging data set to generate a training full dose image and applying the SUV conversion to the training full dose image to generate the training full dose SUV image; generating one or more training low dose emission imaging data sets by sampling the emission imaging data set; reconstructing each training low dose emission imaging data set to generate a training low dose image and applying the SUV conversion to the training low dose image to generate the training low dose SUV image. reconstructing an emission imaging data set to generate a training full dose image and applying the SUV conversion to the training full dose image to generate the training full dose SUV image; generating one or more training low dose emission imaging data sets by sampling the emission imaging data set; reconstructing each training low dose emission imaging data set to generate a training low dose image and applying the SUV conversion to the training low dose image to generate the training low dose SUV image.