Applying Machine Learning Tools for Advanced Image Analysis (starting July 2025)
Detailed workinar content overview:
- Installation of different Software with pre-workshop video guide
- Hands-on Guided Exercises in Microscopic Image Analysis
- Key Concepts, Benefits and Limitations of ML in Image Analysis
- Training Pixel Classifiers for Precise Object Extraction
- Applying Pre-trained Deep Learning (DL) Models to Images
- Deep Learning-Model improvement by human-in-the-loop re-training for Non-Experts
- Simple customized Model Training via user interface-based software for situations where pre-trained models fail.
- Classifying Objects Using Decision Trees for targeted Analysis
- Integrating Fiji (an ImageJ bundle) as Hub for Multiple Software Tools
- Connecting different Tools via Fiji for Streamlined Workflows
All methods are learned hands-on with plenty of practical exercises to get confidence in applying them in your daily work.
Category:
GSP / Data Analysis / Hard Skills
Venue:
The workshop will be held as a virtual live workinar with many hands-on sessions via Zoom.
Duration:
2 days, each day 9:00 to ~15:30 (max, mostly 15:00 but plan some buffer time)
Main Target Group and Focus:
- Life or Natural Scientists starting PhD- or PostDoc-level
- Some practical imaging and image analysis experience is an advantage.
The course focuses on the practical application of existing software on microscopic images! It is not meant for computer scientists, since no computational or programmatic background will be discussed in-depth.
Difficulty Level:
The difficulty level is advanced but even with little prior practical experience it should be possible to follow the step by step procedures and explanation of the necessary background to the individual methods.
Pre-requisites:
Prior participation in the BioVoxxel Workshop – “Basic Microscopic Image Processing and Analysis” is MANDATORY to be able to follow the complete content of this workshop. Participation without prior basic course attendance can only be permitted in exceptional cases in agreement with the trainer and a sound prior knowledge of image processing techniques and ImageJ.
- Computer or Laptop (PC or Mac; supported operating systems: Windows, MacOS and Linux)
- Possibility to install software on your computer (or administrator rights)
- Stable internet connection
- Mouse and Headset/Microphone
- Optimally a webcam
- Best 2 monitors to watch the workinar on one and do the practical part on the other.
- Proficiency in smoothly handling your computer in general is expected
Software:
During the course we will work with a customized version of Fiji (ImageJ bundle). In addition, we will need to install additional software, also Python based software via the command line.
Registered participants will receive all information regarding software preparation on time before the workshop via email.