CZI Workshop I
Center for Open Bioimage Analysis
Introduction to ImageJ
Getting Started with the ImageJ User Application
What is ImageJ?
ImageJ
ImageJ2
Fiji
What is ImageJ?
ImageJ
ImageJ2
Fiji
What is ImageJ?
Fiji is just ImageJ
What can Fiji do?
Tracking
Segmentation
Big Data
Stitching
and more...
Learn how to fish...
GitHub repository:
Teach me how to fish...
Teach me how to fish...
Let’s open/run Fiji...
CTRL + L: Search Bar
Edit ▶ Options ▶ Search Bar... ▶ Pressing L focuses the search bar
The Main Window
Getting Started page of the ImageJ wiki
Staying Up-To-Date
Staying Up-To-Date
Opening Data…
Drag and Drop
File ▶ Open…
File ▶ Import
▶ Bio-Formats
Image Window
Zoom factor (use +/- keys)
Image Type
Image Size in physical units (and pixels)
Dataset positions
File ▶ Open Samples ▶ Mitosis (26MB, 5D Stack)
Bit Depth & Pixel Types
Qualitative/”Just looking”
Quantitative/Measurements
Lookup Tables (LUTs)
Helpful LUTs
Grays
HiLo
Royal
Get to Know Your Data…
ImageJ User Guide: Analyze
What would cause this histogram?
Profile Plots
ImageJ User Guide: Plot Profile
2D Visualization
2D Visualization: Brightness & Contrast
Defining grey value range to be visualized
Thresholding
Isolate grey values of interest
File ▶ Open Samples ▶ Blobs (Shift + B)
Image ▶ Adjust ▶ Threshold…
Which method is best?
Image ▶ Adjust ▶ Auto Threshold, Try All
Regions of Interest (ROI)
Can you draw the same exact circle on a new clown??
Regions of Interest (ROI)
Plugins...
What is a plugin?
A special-purpose software component that extends functionality
There are four tiers of plugins:
Colocalization in Fiji...
Fiji Plugin = Coloc 2
Registration in Fiji...
Feature Extraction
Registration in Fiji...
Feature Extraction
Register Virtual Stack Slices
Registration in Fiji...
TrakEM2
Feature Extraction
Register Virtual Stack Slices
Registration in Fiji...
TrakEM2
Feature Extraction
bUnwarpJ
Register Virtual Stack Slices
Tracking in Fiji
Fiji Plugin = TrackMate
Single particle tracking plugin
Simple/sensible user interface
segmentation / filtering / particle-linking processes visualized in 2D or 3D
extensible...
3D Visualization in Fiji
SciView
plugin for 3D visualization of images and meshes
Uses scenery as rendering backend
Supports rendering to VR headsets via OpenVR
SciView
Segmentation in ImageJ
PART ONE:
The Basics of Segmentation & Machine Learning using ImageJ
What is Segmentation?
What is Segmentation?
The partitioning of a digital image into multiple segments.
Common assumptions/requirements:
Common assumptions/requirements:
2. Do you want to count objects? Or do you want to segment regions?
Common assumptions/requirements:
3. What are the shapes of your objects? Tubes? Blobs? Clouds?
Common assumptions/requirements:
4. What modality was used? And how does the signal look?
Segmentation using Machine Learning...
Segmentation using Machine Learning...
Segmentation using Machine Learning...
Segmentation using Machine Learning...
Helpful Resources: