Access to:
  • 9.5 hours of video content (> 30 videos) and follow-along exercises
  • Several Downloadable Macro Files
  • Get Multiple Unique Fiji Plugins for analysis automation for free (only available in this course)
  • Learn how to efficiently apply and connect ML/DL image analysis tools
  • Course certificate
  • Official invoice after purchase
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
  • Customize your own Deep Learning-Model by human-in-the-loop training for Non-Experts
  • Classifying Objects Using Decision Trees for targeted Analysis
  • Integrating Fiji (an ImageJ bundle) as Hub to connect multiple ML/DL software tools to each other
  • Image batch processing with via Fiji for Streamlined Workflows via all Tools covered
All methods are learned hands-on with plenty of practical exercises and complete analysis examples to get confidence in applying them in your daily work.

Main Target Group and Focus:
  • Life or Natural Scientists starting PhD- or PostDoc-level
  • Some practical imaging and image analysis experience is an advantage.
  • Focus of the examples are images from light microscopy but techniques are applicable to all kinds of images
The course focuses on the practical application of existing software on fluorescent and non-fluorescent (IHC) microscopic images! The same methods can partially also be utilized for electron microscopical images (with some limitations).
The course 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:
  • Some prior knowledge in Basic Microscopic Image Processing and Analysis is advisable
  • 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
  • Computer or Laptop (PC or Mac; supported operating systems: Windows, MacOS and Linux)
  • Possibility to install software on your computer (or administrator rights)
Software:
In this course we will work with a customized version of Fiji (ImageJ bundle). In addition, we will need to install minimally 2 other software packages. This includes python-based software which needs to be installed via the command line.
Please check out the previewable installation lessons of the course before you enroll and see if the software works on your computer system.

Access Period:
  • 36 months from day of purchase (extendable on request)

Course plan

Introduction
Software Installation
Basics on Machine Learning for Image Segmentation
Pixel Classification (using ilastik)
Star-Convex Object Detection in Fiji (fluorescent and RGB)
Combining StarDist and ilastik
Quality Control Metrics
Cellpose - Deep Learning for Everybody
Combining Cellpose and ilastik
3D Image Segmentation
Tracking in Fiji using ML/DL Object Detection
Bonus - Cellpose 4
From Pixels to Patterns