Workinar content overview:
- Proper editing of scientific images for publications and good scientific image handling practice
- Understanding all aspects of digital images (e.g. metadata, bit depth, histogram,…)
- Scaling, scale bars, false colors, calibration bars, …
- Uneven lighting correction methods for visualization and processing
- Diverse background correction algorithms and their proper application
- Image pre-processing: understanding image filters, their properties and usage
- In-depth object extraction and optimizing image segmentation
- Image post-processing: morphological operations for increased reliability during analyses
- Analysis: object counting, size and shape determination, ROI-based intensity quantification
- Assembly of process automation: A brief introduction to ImageJ macros
All methods are kept as general as possible to achieve a broad applicability. Very specific image analysis techniques (such as co-localization etc.) are part of an advanced course
The workshop will be held as a virtual live workinar with many hands-on sessions via Zoom.
3 days, each day 9:00 ~ 15:30(max, mostly 15:00 but plan some buffer time)
Main Target Group and Focus:
Life or Natural Scientists (optimally around PhD student level and above, imaging experience is helpful but not necessary). Independent of the scientific background, everybody is invited to join if interested in the topic.
It has a very strong focus on fluorescent micrographs! However, the methods taught are not limited to those and applicable to other image material as well. It is designed application-based to learn and apply basic image processing and analysis in daily research. It is not an algorithm-based teaching for computer scientists.
The course is recommended mainly to scientists working with (fluorescent) microscopical samples, are planning to do so or are generally interested in this area of image analysis.
The difficulty level is basic to medium and easy to follow in step by step procedures and in-depth explanation of the necessary background to the individual methods. Also scientists with some prior knowledge will still benefit from the methods taught, especially in the image analysis section of the course.
- Computer or Laptop (PC or Mac; supported operating systems: Windows, MacOS and Linux)
- 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.
During the course we will use exclusively Fiji (ImageJ bundle) in a customized setup. Prior software knowledge is not required but might be of advantage.
Registered participants will receive all information regarding software preparation on time before the workshop via email.