Microscopie à épi-fluorescence et microscopie confocale: Des bases à la pratique
The use of fluorescence microscopy (wide field, confocal, multiphoton, and now superresolution) in combination with genetically encoded fluorescence probes comprise a powerful set of scientific tools to study live cells. However, surprising little practical and theoretical training in such methods exists within standard curricula, particular at the early stage of training (Masters or Doctorate level). This course offers to cover basic optics principles necessary to understand the origin of microscope resolution and design. Participants will get hands-on experience implementing simple optical configurations to illustrate these fundamental principles. Subsequently, participants will perform experiments on state-of-the-art imaging equipment provided by microscope vendors.
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.
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.