Net (polyhedron)

Plug-in

Operating system

Computer science

Cloud computing

Image segmentation

Segmentation

Pattern recognition (psychology)

Mathematics

Artificial intelligence

Geometry

Deep learning

Machine learning

Computer vision

Nature Methods

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. A user-friendly ImageJ plugin enables the application and training of U-Nets for deep-learning-based image segmentation, detection and classification tasks with minimal labeling requirements.

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