deepImageJ
Trainer: ilastik team, Esti Gomez De Mariscal and Dominik Kutra
This session was a part of the 2023 iteration of this course.
Overview: DeepImageJ is a user-friendly plugin that enables the use of a variety of pre-trained neural networks in ImageJ and Fiji. The plugin bridges the gap between developers of deep-learning models and end-users in life-science applications. It favors the sharing of trained models across research groups and could have a broad impact in a variety of imaging domains. DeepImageJ does not require any deep learning expertise or any computer programmer skills. This session covers key aspects of this plugin.
Learning outcomes:
After this session you should be able to:
- Identify how to bring pre-trained models from the BioImage Model Zoo to end-user software and use these models
- Perform segmentation of cell images
- Run super-resolution models in Fiji
Materials: