UNet is a state-of-the-art CNN based architecture typically used in segmentation tasks. I have used this for semantic segmentation of Anterior and Posterior Views of Human Spine. The catch here is that the architecture is trained on just 30-90 masks and can be as large as 30 million parameters and yet achieves an IoU >70. - View it on GitHub