Syllabus
Lesson 1: Image Formation in microscopy modalities, resolution and super-resolution, noise, image dimensions, file formats, workflows, image preprocessing, image restoration, image processing, segmentation, object classification, measurements, statistics, data visualization, data management, FIJI introduction.
Lesson 1: Basic image handling in FIJI
Lesson 2: Preparing images for analysis
Lesson 3: Basic measurements and image segmentation
Lesson 4: Machine learning techniques and advanced image processing and segmentation
Lesson 5: CLIJ GPU accelerated analysis, FIJI customization
Lesson 6: Introduction to macro language, scripting, and batch processing
Lesson 7: Programming fundamentals, writing scripts in macro language
Lesson 8: Writing custom scripts for batch analysis
Lesson 9: Colocalization analysis
Lesson 10: Advanced microscopy techniques analysis and image processing
Lesson 11: Implementation FIJI in large workflows, using imageJ in computing cluster
Lesson 12: Students projects presentation
Annotation
This course will provide a comprehensive understanding of the usage of the open-source software ImageJ for scientific image analysis. The course will cover everything from basic manipulations to custom scripting.
Students will learn how to create functional workflows for the analysis. The course is suitable for total beginners as well as for intermediate users.
The course will be held in hybrid mode for a maximum of 20 students in personal attendance and virtually unlimited students online.