DeepImageJ

The ImageJ plugin to run deep-learning models

DeepImageJ is a user-friendly plugin that enables the use of a variety of pre-trained deep learning models in ImageJ. The plugin bridges the gap between deep learning and standard life-science applications. DeepImageJ runs image-to-image operations on a standard CPU-based computer or on GPU, and does not require any deep learning expertise.

Visit the DeepImageJ website at https://deepimagej.github.io/deepimagej

Conditions of use

The DeepImageJ project is an open source software (OSS) under the BSD 2-Clause License. All the resources provided here are freely available.

As a matter of academic integrity, we strongly encourage users to include adequate references whenever they present or publish results that are based on the resources provided here.

References

• If you used one of the material provided within DeepImageJ such as trained models or Python notebooks, cite their authors' work.
• Gómez-de-Mariscal, E., García-López-de-Haro, C., Ouyang, W., Donati, L., Lundberg, L., Unser, M., Muñoz-Barrutia, A. and Sage, D., "DeepImageJ: A user-friendly environment to run deep learning models in ImageJ", Nat Methods 18, 1192–1195 (2021). https://doi.org/10.1038/s41592-021-01262-9
  • Read the paper online with this link: rdcu.be/cyG3K