Automating machine learning segmentation and restoration in ImageJ / Fiji

This tutorial focuses on utilizing machine learning tools within ImageJ/Fiji to create powerful and rigorous automated analysis pipelines.

This tutorial includes:
0:00 - Overview of machine and deep learning
14:48 - Using Ilastik for pixel and object classification
33:58 - Combining Ilastik with macros for automation
40:29 - Using StarDist for cell segmentation
47:06 - Installing and using DeepImageJ
53:53 - Training your own network using CSBDeep

For a better understanding of how to create and use ImageJ/Fiji macros, we recommend watching this video first: Automating analysis with Fiji (ImageJ)

If you are just starting to use Fiji, try watching our first workshop, which introduces Fiji and includes time-saving steps to make image processing easier and more efficient:
Introduction to using Fiji (ImageJ)

Data used in this workshop is available here: https://www.dropbox.com/sh/czk9oxsbb2...
Scripts created during this workshop are available here:
https://github.com/lahammond/CI_Image...

Recorded on Thursday, November 11, 2021, as part of Cellular Imaging's 2021 Image Analysis Program by Luke Hammond (Director of Cellular Imaging, Zuckerman Institute, Columbia University)

https://www.cellularimaging.org/

• #science_technology
• #imagej
• #imageprocessing
• #imageanalysis
• #fiji
• #machine_learning
• #image_processing
• #image_analysis
• #deep_learning