Conditional three-dimensional (3d) denoising of positron emission tomography (pet) images

A system comprising

• one or more processors and
• one or more non-transitory computer readable media storing processor-executable instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:
• receiving a low-dose positron emission tomography (PET) image;
• providing the low-dose PET image as a conditional input to a neural network model of a plurality of neural network models trained using a three-dimensional denoising diffusion probabilistic model (3D DDPM), wherein the neural network model comprises a score function that corresponds to a training of the neural network model based on three-dimensional distribution information of a plurality of normal-dose PET images that comprises a desired image quality;
• and
• providing the low-dose PET image to the neural network model to produce a denoised PET image, wherein the denoised PET image is iteratively reconstructed from the low-dose PET image during a reverse diffusion process in accordance with the score function.

One or more non-transitory computer-readable storage media storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving a low-dose positron emission tomography (PET) image;
• providing the low-dose PET image as a conditional input to a neural network model of a plurality of neural network models trained using a three-dimensional denoising diffusion probabilistic model (3D DDPM), wherein the neural network model comprises a score function that corresponds to a training of the neural network model based on three-dimensional distribution information of a plurality of normal-dose PET images that comprises a desired image quality;
• and
• providing the low-dose PET image to the neural network model to produce a denoised PET image, wherein the denoised PET image is iteratively reconstructed from the low-dose PET image during a reverse diffusion process in accordance with the score function.