PPBI
Batch analysis and macro development in ImageJ/Fiji: going beyond the basics | 2nd edition
9, 10, 11, 14 and 15 December 2020 | ONLINE COURSE
This course is designed for ImageJ/Fiji users who want to go beyond the basics and progress to more intermediate/advanced analysis with this software. The course will focus on how to automate routine tasks (for conditions where many images need to be processed), as well as how to deal with more complex image analysis situations, to maximize information extraction.
Although ImageJ can be used with its graphical user interface, the implementation of a workflow to multiple images requires the development of macros and/or scripts for batch processing. At the course, this process is tackled by building up from the development of very simple macros to more complex workflows, where images are processed and information acquired in an automated or semi-automated way.
Previous knowledge on the basics of bioimage analysis is recommended, but no prior experience in ImageJ macro development is required or assumed, nor any prior programming skills.
CONTENTS
- Introduction to batch analysis: from macro recorder to simple scripts.
- ImageJ macro language syntax.
- From GUI (graphical user interface) workflows to scripts: exploring ImageJ’s built-in functions and developing user-defined functions.
- Automatic data loading: access-list of files in a given directory and filter it by text patterns in file name or by extension.
- Batch processing from scripts.
- Combine multi-dimensional information: programmatically identifying image pairs (e.g. multichannel, time-lapse) and combine information.
- From Image data to tables: extract information to tables and personalize output variables on output tables (data logging).
- Export sample images and customized tables to a directory.
More information and registration: https://www.i3s.up.pt/training?v=118
BioImage Analysis for High Content Screening
25-28 May 2021 | i3S
High Content Screening generates a massive amount of image-based data in the biosciences field. Images contain diverse and valuable quantifiable data, however, many researchers lack the knowledge to extract those data in a practical, fast and repetitive way. Fundamentally practical, in this modular course, participants will get acquainted with several open-source image analysis software (ImageJ/Fiji, ilastik, CellProfiler, CellProfiler Analyst, Cytoscape and IDEAS®) designed to deal with large amounts of images. Experimental data will be used as datasets for image segmentation and quantification.
This course is organized in modules. Therefore, participants are free to choose the image analysis tools more convenient to their own work.
CONTENTS
- High content image analysis
- Image segmentation and quantification
- Batch analysis
- Open-source image analysis software
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