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/