Description of the training activity
Bioimage analysis has become a keystone of biological research: the deluge of data produced by increasingly advanced microscopes calls for experts able to guide life scientists in the methods and software to be used to produce quantitative knowledge from this data. Due to the complexity of the data, without such expert guidance, it is very likely that image analysis algorithms may be applied incorrectly, possibly even producing erroneous results. Moreover, the diversity of imaging modalities, analysis algorithms and software solutions is growing so rapidly that even experts are overwhelmed.
This advanced course concentrates on teaching cutting-edge concepts and tools for quantitative image analysis, and will seek to upgrade the competencies of future bioimage analysis experts on both theoretical algorithm advancements as well as on practical implementation skills.
Learning outcomes of the training activity
- Microscopy image quality control and image restoration
- Advanced image segmentation and complex cell phenotyping
- Handling large microscopy images (such as whole slide scans) and big N-dimensional data
- Neural-networks for image restoration, segmentation, and object classification.
- Co-localisation and spatial statistics
- Train the trainer: how to teach image analysis
For each module, participants will learn both theoretical and practical aspects. In addition, participants will gain new insights about how to set up an image analysis course in their own institution.