Under an initiative by EPFL's Center for Imaging, a team of engineers from EPFL and Universidad Carlos III de Madrid have developed a plugin that makes it easier to incorporate artificial intelligence into image analysis for life-science research. The plugin, called deepImageJ, is described in a paper appearing today in Nature Methods. Over the past five years, image analysis has been shifting away from traditional mathematical- and observational-based methods towards data-driven processing and artificial intelligence. This major development is making the detection and identification of valuable information in images easier, faster, and increasingly automated--in just about every research field. When it comes to life science, deep-learning-, a sub-field of artificial intelligence, is showing an increasing potential for bioimage analysis.

DeepImageJ has been updated to DeepImageJ 2.1. The format of the models in previous versions are not compatible with DeepImageJ 2.1. Please, try to update your models using DeepImageJ Build Bundled Model or do not update DeepImageJ in Fiji using the Update Sites until you can update your models. Contact us if you have any question! DeepImageJ is a user-friendly plugin that enables the use of a variety of pre-trained deep learning models in ImageJ and Fiji.