METHOD FOR GENERATING RARE MEDICAL IMAGES FOR TRAINING DEEP-LEARNING ALGORITHMS

The invention relates to a method for generating synthetic medical images representing an anatomy of interest and an anomaly within said anatomy of interest. The method comprises generating majority segmentation masks associated with real medical images without anomaly, generating minority segmentation masks associated with real medical images with an anomaly, training a neural network to generate a synthetic medical image on the basis of a segmentation mask, generating artificial segmentation masks on the basis of the majority and minority segmentation masks by combining a segmentation of the anatomy of interest by a majority segmentation mask with a segmentation of the anomaly by a minority segmentation mask, and generating synthetic medical images on the basis of the artificial segmentation masks and using the previously trained neural network.