Abstract: Automatic registration of multi-modal coronary imaging data is disclosed. First imaging data acquired using a first modality (e.g., positron emission tomography (PET) imaging) is applied to a neural network to output pseudo imaging data that is associated with a second modality (e.g., computed tomography (CT) imaging). The pseudo imaging data is then compared with (e.g., via nonlinear diffeomorphic registration) second imaging data acquired using the second modality to generate transformation information. This transformation information can then be applied to the first imaging data or other imaging data acquired in the first modality to register that imaging data with the second imaging data or other imaging data acquired in the second modality.