Course Description
ilastik is a free, open-source, and truly user-friendly image analysis tool that can help you leverage machine learning algorithms to easily segment, classify, track, and count your cells or other experimental data. Most operations are interactive, even on large, multi-dimensional datasets: you just draw the labels and immediately see the result. No machine learning expertise required. In this course you will learn how to perform automated pixel- and object-level segmentation, object classification, and tracking.
Using ilastik requires no previous experience in image processing. This course is aimed at anyone who works with biological images and wants to learn to use ilastik to easily process and analyse their data.
Course Content
Morning
- Introduction to machine-learning based image analysis
- Introduction to ilastik
- ilastik workflows
- Pixel Classification
- Autocontext
- Neural Networks Prediction
Afternoon
- ilastik workflows
- Object Classification
- Multicut
- Tracking
- Automation
- Batch processing
- Fiji integration
- Command line usage
- Jupyter notebook usage
- Running on embl resources
Registration
Registration is required, via the booking form below. All tickets are for remote attendance.
Prerequisites
The course assumes no prior experience with ilastik. It will be hands-on: you should use your own laptop with ilastik installed (see link below for installation instructions). And please have a computer mouse ready.