This school targets bioimage analysts, who are willing to enhance their professional scope and techniques for improving the quality of their analysis, as well as willing to contribute with their knowledge and experience to the school. Prerequisite is a proficiency in at least one programming language (we do not train coding). The school focuses on workflow designing. This year, we will have a particular emphasis on statistics for bioimage analysis and related tools e.g. R and Python libraries. In addition, we will overview machine & deep learning components.
This training school will cover the basics of image analysis using ImageJ/Fiji, as well as image analysis workflow automation using ImageJ macro programming. In addition, it will be taught how to use the software package ilastik for machine learning based image segmentation and object classification, and how to integrate ilastik into ImageJ macro based workflows. Moreover, an overview of further relevant bioimage analysis software packages will be given and there will be ample time for "Work on Your Own Data" sessions assisted by experienced Analysts.