Access to:
- Over 17 hours of videos (~50 video)
- Over 30 practical hands-on exercises with step-by-step instruction
- Good scientific practice based methods and background info
- Application example files for download (also as orientation for own image analysis)
Course Content Summary:
- Short Introduction to Fiji / ImageJ and basic functions
- Overview over proper scientific image file formats, metadata, bit depth
- In-depth practical introduction to pre-processing
- Automatic uneven lighting correction
- Understanding of image filters and their use cases for improved object detection
- Automatic background subtraction algorithms to reduce unspecific signal
- Object segmentation with automatic intensity thresholds (semantic segmentation)
- Individual object labeling (instance segmentation)
- Basic insight into some user friendly machine learning plugins in comparison to classical segmentation
- Optimization of segmentation with post-processing methods
- Quality control of segmentation results
- Different basic automatic analyses (object counting, measurements, shapes, intensities)
- Short introduction to macro recording for automation.
- Bonus 1: Insight into 3D image segmentation and related important considerations
- Bonus 2: Insight into object Tracking in Fiji
- Bonus 3 Downloadable automatic image analysis examples to better understand the application of the learned.
All methods are learned hands-on with plenty of practical exercises to get confidence in applying them in your daily work.
Main Target Group and Focus:
Life or Natural Scientists starting at the level of undergraduate students with no upper limit. Independent of the scientific background, everybody is invited to join if interested in the topic.
Optimally, some practical imaging experience is an advantage but not necessary.
Additional Note:
The course has a very strong focus on fluorescent microscopic images but discusses also Color images such as immunohistochemical samples or photographs!
Difficulty Level:
The difficulty level is 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.
Pre-requisites:
- Computer or Laptop (PC or Mac; supported operating systems: Windows, MacOS and Linux)
- Stable internet connection
- Computer mouse
- Optimally, 2 monitors to watch the workinar on one and do the practical part on the other
- Proficiency in handling your computer in general
- Possibility to install software on your computer (or administrator rights)
During the course we will exclusively work with a customized version of Fiji (ImageJ bundle) Fiji is free of charge, accessible for everybody and open source. Prior software knowledge is not required but might be of advantage.
Access Period:
- 36 months from day of purchase (extendable on request)
Course plan
Introduction
Course Preparations
Before You Start - Important Core Concepts!
Let's directly jump in
Introduction to Image Segmentation
Pre-Processing
Segmentation - Thresholding
Assignment - Image Segmentation
Machine Learning - Pixel Classification as Alternative to Thresholding
Post-Processing
Image Analysis and Measurements
Macro Recording and Automation
Color Image Segmentation
Bonus 01 - 3D Image Segmentation
Bonus 02 - Analyzing Time Series (Tracking)
Bonus 03 - Application: Practical Analysis Examples
Basic Image Analysis
