U-Net: deep learning for cell counting, detection, and morphometry

Nat Methods. 2019 Jan;16(1):67-70. doi: 10.1038/s41592-018-0261-2. Epub 2018 Dec 17.


U-Net is a generic deep-learning solution for frequently occurring quantification tasks such as cell detection and shape measurements in biomedical image data. We present an ImageJ plugin that enables non-machine-learning experts to analyze their data with U-Net on either a local computer or a remote server/cloud service. The plugin comes with pretrained models for single-cell segmentation and allows for U-Net to be adapted to new tasks on the basis of a few annotated samples.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Count*
  • Cloud Computing
  • Deep Learning*
  • Neural Networks, Computer
  • Software Design