Meeting Banner
Abstract #4055

MRI image synthesis with a conditional generative adversarial network using patch pooling

Bragi Sveinsson1,2 and Matthew S Rosen1,2,3
1Martinos Center, Massachusetts General Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Physics, Harvard University, Cambridge, MA, United States

Deep learning networks allow the creation of new images based on a separate set of reference image data. This can be used to synthesize a specific MRI contrast from other image contrasts sharing the same anatomy. A particularly successful approach uses a conditional generative adversarial network with a patch-based discriminator, processing image patches of a fixed size. In this work, we investigate the benefits of using multiple patch sizes to improve image quality.

This abstract and the presentation materials are available to members only; a login is required.

Join Here