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This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualization, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

On day 3, we will cover time series processing and cell tracking using TrackMate. In the afternoon, we will present the Image Data Resource, an added-value platform that combines data from multiple independent imaging experiments and imaging modalities and integrates them into a single resource for reanalysis in a convenient, scalable form.



  • Researchers who are applying or planning to apply image analysis in their research
  • Basic skills in mathematics and programming are an advantage, but not a requirement.


For additional information, follow this link.