For segmentation (32) in medical imaging, a shape generative adversarial network (shape GAN) (45) is used in training (12). By including shape information in a lower dimensional space than the pixelsor voxels of the image space, the network (45) may be trained (12) with a shape loss or optimization. The adversarial loss and the shape loss are used to train (12) the network, so the resulting generator may segment complex shapes in 2D or 3D. Other optimization may be used, such as using a loss in image space.
SHAPE-BASED GENERATIVE ADVERSARIAL NETWORK FOR SEGMENTATION IN MEDICAL IMAGING