Abstract: A computer-implemented method for determining cardiac functional indices for a patient including: receiving an image of a fundus of the patient; encoding the received image into a joint latent space; decoding from the joint latent space a representation of the patient's heart; providing the representation decoded from the joint latent space to a neural network configured to generate cardiac functional indices; and outputting the cardiac functional indices generated by the neural network in response to receiving the decoded representation of the patient's heart.

Abstract: There is provided a computer-implemented method for synthesising magnetic resonance angiography (MRA) images from other types of inputted magnetic resonance (MR) images, in a subject-specific manner, the method comprising providing a conditional generative adversarial network (cGAN) that learns a combined latent representation of the inputted magnetic resonance images for each subject and learns to transform this combined latent representation to a magnetic resonance angiography image corresponding to that subject, providing a plurality of magnetic resonance (MR) images as input into the cGAN, and outputting a plurality of MRA images from the cGAN based on the plurality of inputted MR images.