Patent ID: 11935238
Assignee: REALIZEMD LTD.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 3:
4. The computer implemented method of claim 1, wherein generating the synthetic image comprises:
computing, for each respective real image, a respective set of real latent vectors within a latent space of a pretrained generative adversarial network (GAN) using a GAN inversion approach;
analyzing each respective set of real latent vectors to identify data representing at least one adaptable attribute;
computing, for each respective synthetic image depicting the synthetic human anatomical structure, a respective set of synthetic latent vectors within the latent space of the pretrained GAN using the GAN inversion approach;
adapting each respective set of synthetic latent vectors, to include the data representing the at least one adaptable attribute obtained by the analysis of the respective set of real latent vectors;
reconstructing each respective synthetic image from a corresponding respective set of adapted synthetic latent vectors,
wherein each synthetic image that includes the respective synthetic image reconstructed from the respective set of adapted synthetic latent vectors depicts the at least one adaptable attribute, as depicted by the corresponding real image, wherein the at least one adaptable attribute is easily adapted by the real human anatomical structure, the at least one adaptable attribute selected from a group consisting of: body pose, limb pose, blood flow phase, muscle contraction or relaxation, and lighting.