Contents
Image Analysis Fundamentals
This is a two-day course for the master students of the Department of Biosystems Science and Engineering at the ETH Zurich.
Course content
First day
- Course introduction
- Introduction to Fiji
- Image processing/analysis fundamentals (with selected examples/demos in Fiji)
- Deconvolution (with HRM hands-on)
- Scripting in Fiji
Second day
- Cell Profiler
- ilastik
- Good practices in scientific image analysis
- Analysis hands-on
- Selected libraries (quick presentation and demo)
- MATLAB: Image Processing Toolbox
- Python: scikit-image, openCV
Course material available on request.
Digital images (Linear shift-invariant systems)
An introduction to signals and systems, sampling theory, filtering in spatial and frequency domain.
First presented at the Image Processing basics course organized by the Microscopy Network Basel in November 2014 (last update: November 2016).
Deconvolution primer
This is a short introduction to optics, image formation, and deconvolution that I give before an hands-on course on the Huygens Remote Manager (last update: November 2016).
Introduction to ImarisXT and IceImarisConnector
Extending Imaris with custom MATLAB functions:
- Course text
- XTensions
- dataset [8.7MB]
Extract from Imaris Open Launch talk:
Biological Image Processing Summer School 2010
Focused on ImageJ, MATLAB and Cell Profiler
In collaboration with the (former) Light Microscopy Centre, ETH Zurich
August 29th – September 3rd, 2010
Role: co-organizer of the scientific program and teacher
Introduction to MATLAB programming
Course material
- Session 1: First steps in MATLAB (exercise solutions)
- Session 2: Data types and structures (exercise solutions; MATLAB code)
- Session 3: Object-oriented programming and external interfaces (add-on; MATLAB code)
- Session 4: Visualization and GUI programming (MATLAB code)
Introduction to statistics with MATLAB
Course material
This course had its own introduction to MATLAB, but I recommend using sessions 1 and 2 (and maybe even 3) from the “Introduction to MATLAB programming” course above.
Source control with Subversion
Quick introduction to source control using subversion.