A GAN-based contrast-agent-free medical image enhancement modeling method, relating to the technical field of medical image processing. The method comprises: using a GAN enhancement algorithm to generate a virtual contrast-agent image of a previous patient according to a contrast-agent-free image of the previous patient; training the virtual contrast-agent image with a real contrast-agent image of the previous patient to obtain a final virtual contrast-agent image of the previous patient; and fusing the final virtual contrast-agent image and the contrast-agent-free image of the previous patient, and establishing an image target analysis model. An established virtual contrast-agent image model allows for obtaining of the virtual contrast-agent image without taking a contrast agent by a newly added patient, simplifies a treatment process, and reduces treatment costs of the patient.
GAN-BASED CONTRAST-AGENT-FREE MEDICAL IMAGE ENHANCEMENT MODELING METHOD