Processing Images Using the Free and Open-Source Software Icy

This tutorial presents how to investigate an image, by extracting quantitative information. This tutorial is presented as an interactive study which is performed live, using Icy. The audience will participate and will propose interpretation of the problem, and of course, there will be a lot of traps! It covers a large number of topics: understanding the nature of noise in the image, understanding the interest of different representations of the images: the richness of 2D and 3D rendering in different modalities, the use of color maps and the practical use of histograms. In a second step, more advanced algorithms such as wavelets for spot detection and MHT for tracking of particles are also covered.

During this presentation, a number of Icy's functionalities are covered: visualization, use of ROI, histogram, look up table, running and installing plugins, scripting in JavaScript and Python, graphical scripting using protocols, management of data, method reusability and how to reach unknown functionalities.

Students coming to this session will learn in a didactic and ludic way why the noise is so important in the images and what the good practices of the image analysis are. In this interactive session, they will discover that one needs to deeply understand his/her data before performing an analysis. Each step performed during this tutorial is reproducible since the software and the data are free and available for download. At the end of the session, the attendants can perform and extend their analysis directly on their laptops!

Course Details or Outline:

  1. Installing Icy
  2. Opening an image
  3. Understanding the histogram and the look up table (color map)
  4. Finding functionalities in seconds without knowing the software!
  5. The ImageJ compatibility.
  6. Website presentation, browsing script resources and graphical protocols.
  7. The screen is lying to us! Representation of 16bits images.
  8. Interpreting an atomic force microscopy output as an image.
  9. Viewing background information
  10. Viewing data that cannot be displayed in 2D with false color map.
  11. Characterization of noise
  12. Using a 3D ray-traced volume rendering vs a 3D elevation map rendering
  13. Interpretation of the histogram
  14. Data are lying to us: understand the defects of the data acquisition
  15. Detecting density of spots representing neurons in an image
  16. Automatically perform segmentation of cell in an image, and then density detection
  17. Interpreting results
  18. Interpreting results of several users over the same sample
  19. Detection of vesicle and tracking
  20. Description of global and individual movements
  21. Concluding remarks

Processing Images Using the Free and Open-Source Software Icy

Speaker Information
Fabrice de Chaumont   [ view bio ]
Individual topic purchase: Selected
American Society for Clinical Pathology
CMLE: 1.50
This continuing medical laboratory education activity is recognized by the American Society for Clinical Pathology for 1.5 CMLE credit. ASCP CMLE credits are acceptable for the ASCP Board of Registry Certification Maintenance Program.
International Society for Advancement of Cytometry
ICCE: 1.50
This Seminar is presented free of charge.