Continuous U-Net: Faster, Greater and Noiseless

Understand

Image segmentation is a fundamental task in image analysis and clinical practice.

• The current state-of-the-art techniques are based on U-shape type encoder-decoder networks with skip connections, called U-Net.
• Despite the powerful performance reported by existing U-Net type networks, they suffer from several major limitations.
• Issues include the hard coding of the receptive field size, compromising the performance and computational cost, as well as the fact that they do not account for inherent noise in the data.