This one-week school provides a hands-on introduction to image processing and analysis, with an emphasis on biologically relevant examples.
Covered topics will encompass :
- Basics in Image Formation
- ImageJ, from everyday use to advanced applications
- State-of-the-art analysis procedures like e.g. co-localisation
- Machine Learning including Deep Learning
- Stitching and registration
- Data analysis using KNIME
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.
This training session will cover the basics of super resolution in photonic microscopy, principally: STED microscopy (STimulated Emission Depletion) and single molecule localization microscopy. We will also present alternative solutions for super resolution like SRRF (Super resolution Radial Fluctuations), Airy Scan, or Computer based pixel-reassignment like ISM (Image Scanning Microscopy), and solution based on light sheet illumination. The mornings will be dedicated to theoretical lectures and application seminars. The afternoons will allow the participants to see demonstrations of these different techniques in front of home-made or commercial systems. The fourth day will be a full hands-on day, as participants will be invited to bring their own samples and test them on the different systems available, like STED microscope, STORM, lattice light sheet, ISM, SRRF….
The workshop will last 3 ½ days and is built on the basis of an alternation between theoretical and practical sessions. Both will be in English and provided by national expert trainers.
On day 2 a mini-symposium will be organized to present the last developments in different LSFM domains (instrumentation, sample preparation and data analysis) done by international experts. This mini-symposium will be open to a larger audience in order to promote LSFM approaches to the local research community.
The workshop will encompass various theoretical aspects of LSFM from sample preparation, to image acquisition and first post-processing steps (3D reconstruction, visualization).
The workshop will span various scales that can be imaged with LSFM based on at least 4 different LSFM set-ups.
Rapid advances in live imaging of targeted cellular morphologies and functions underpin the emerging revolution in our understanding of synapses, circuits, and behaviour. In keeping with its long-established tradition, this Cajal course will assemble at its international faculty leading experts in developing and exploiting cutting-edge imaging techniques that have been propelling such advances. How to combine genetically encoded fluorescence labelling with behavioural designs, micro-circuit monitoring, or single-molecule tracking, how to avoid pitfalls of having false-positive observations and inherent noise, how to best analyse your multi-dimensional data will be, among others, the recurrent subjects of the Course.
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.
Microscopie à épi-fluorescence et microscopie confocale: Des bases à la pratique