Sign In

JoVE Journal

Bioengineering

A subscription to JoVE is required to view this content.

Automation of the Micronucleus Assay Using Imaging Flow Cytometry and Artificial Intelligence

1.7K Views

09:11 min

January 27th, 2023

January 27th, 2023

1,728 Views

0:05

Introduction

0:49

Creating an Experiment in the Artificial Intelligence (AI) Software

2:41

Populating the Ground Truth Data Using A‐Assisted Tagging Tools and Training the Model

4:11

Classifying Data Using the Model and Generating Report

6:28

Results: Validation of the AI‐Assisted Cluster and Predict Algorithms

8:23

Conclusion

Transcript

Performing the micronucleus assay using imaging flow cytometry overcomes many limitations of traditional methods, including low throughput, score variability, and lack of visual confirmation of events. The main advantage of this technique is that

Sign in or start your free trial to access this content

The micronucleus (MN) assay is a well-established test for quantifying DNA damage. However, scoring the assay using conventional techniques such as manual microscopy or feature-based image analysis is laborious and challenging. This paper describes the methodology to develop an artificial intelligence model to score the MN assay using imaging flow cytometry data.

We use cookies to enhance your experience on our website.

By continuing to use our website or clicking “Continue”, you are agreeing to accept our cookies.

Learn More