Foveal fully convolutional nets for multi-organ segmentation

This paper proposes a novel fully convolutional neural network architecture for image segmentation and shows that the same architecture with the same learning parameters can be used to train models for 20 different organs on two different protocols, while still achieving segmentation accuracy that is on par with the state-of-the-art.