Course description:

This course is aimed at participants familiar with the basics of image processing, who want to automate their analysis using scripting. We will work with ImageJ macro language and use it to create a workflow for segmentation, batch processing and analysis of fluorescence microscopy images. In the second part of the course, we will introduce Cellpose, a machine learning algorithm for cell segmentation, demonstrate its use through command line and ImageJ plugin, and incorporate its output into the ImageJ workflow.

No previous programming knowledge is expected, and the course will therefore also briefly introduce basic programming concepts, such as variables, for loops and conditionals (if-else statements). Most of the sessions will be hands-on, and the last day will be dedicated to individual consultations of user projects and questions.

Target audience:

The course is primarily aimed at participants with some experience with ImageJ and basic understanding of bioimage analysis. We expect no or minimal knowledge of programming.

Requirements:

Participants are required to bring their own laptop for hands-on exercises. If you do not have access to a laptop, please inform us in advance, and we will provide you with one. Prior to the event, you will receive a list of the required software programs to install for the course.

Please make sure that all required software is installed and works prior to the workshop, especially if your laptop runs macOS or Linux (we work mostly with Windows and are therefore not as familiar with the other operating systems, therefore troubleshooting during the course is difficult).

Program and more information: