The summer school is structured around 7 sessions, each covering a specific imaging topic (see below).
There will be one to two sessions per day, each consisting of lectures and interactive practical works on the current thematic.
- Fundamentals of Scientific Images
- Key concepts in digital imaging (pixel level, contrast, histogram, file format, etc.), multidimensional data (visualisation)
- Image Acquisition
- Optics of image formation (light sources, PSF/MTF, etc.), noise, SNR, resolution, 3D scenes, stereo imaging
- Operations on Digital Images
- Digital filters, morphological operators, segmentation
- Motion Tracking
- Optical flow and registration, measuring a displacement field (local, global, discrete), representing and quantifying deformations, tracking of particles (detection and linking)
- Machine Learning for Image Analysis (1/2)
- Key terminology, data preparation, existing ML software for image analysis
- Machine Learning for Image Analysis (2/2)
- Building and training of models, running of pre-trained models, fine-tuning of pre-trained models
- Good Practice for Open Imaging
- Ethics of image publication, the do’s and don’t of figure preparation, storage, formats, licenses, open access, confidentiality
Please click on the link below to see the full schedule of the summer school.