U-Net Resources

What is U-Net?

The u-net is convolutional network architecture for fast and precise segmentation of images. Up to now it has outperformed the prior best method (a sliding-window convolutional network) on the ISBI challenge for segmentation of neuronal structures in electron microscopic stacks.

Why we need U-Net?

It has won the Grand Challenge for Computer-Automated Detection of Caries in Bitewing Radiography at ISBI 2015, and it has won the Cell Tracking Challenge at ISBI 2015 on the two most challenging transmitted light microscopy categories (Phase contrast and DIC microscopy) by a large margin (See also our annoucement).

Visit the following resources to learn more:

• Convolutional Networks for Biomedical Image Segmentation

• Semantic segmentation

• U-net architecture

Convolutional Networks for Biomedical Image Segmentation:

• Article describing U-net

• Segmentation

U-Net offers:

• Autoencoder Architecture