Utilizing AI-Driven Analysis to Enhance Dynamic Cell Health Insights
Last updated: August 7, 2023
Overview
Live-cell imaging enables the acquisition of phase contrast and fluorescent images in a non-perturbing manner. Alongside the incorporation of Artificial Intelligence (AI) into image analysis workflows, this has empowered accurate quantification of a broad spectrum of cellular models, making it a powerful approach to aid data-driven decisions. These innovative technologies, based on neural network algorithms, are more complex than traditional image analysis and facilitate more accurate segmentation of heterogenous cell morphologies whilst minimizing user-introduced bias.
In this video we will discuss the recently launched Incucyte® AI Cell Health Analysis software module. The integrated software is powered by pre-trained neural networks and is a robust solution for label-free segmentation and Live/Dead classification of individual cells. We exemplify how this AI driven approach can be used in combination with optional fluorescent readouts to enhance insights into cell health and function, including phagocytosis, caspase-dependent apoptotic pathways, and cell cycle perturbance.
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- Document type: Webinar
- Watch time: 10 minutes
Key Takeaways
Learn more about:
- Combining live-cell imaging and AI into image analysis workflows, creating a powerful approach to aid data-driven decisions
- Why these innovative technologies, based on neural network algorithms, facilitate more accurate segmentation of heterogenous cell morphologies whilst minimizing user-introduced bias
- Performing AI Cell Health optional fluorescence analysis to gain additional information into cell health and function
Figure 1. Live-Live-cell imaging enables the acquisition of phase contrast and fluorescent images in a non-perturbing manner. This poster introduces the Incucyte® AI Cell Health Analysis software, an artificial intelligence (AI)-driven approach to label-free segmentation and live/dead cell classification.
Webinar Speakers
Jasmine Trigg
Jasmine Trigg is currently a scientist at Sartorius with the cell imaging and applications group of the Bio Analytics team. She has worked across multiple research areas developing cellular assays to extend the suite of live-cell analysis applications. Jasmine has a background in neuroscience and genetic manipulation, and her earlier work focused on using a combined structural and molecular biology approach to assess disease-associated proteins implicated in Alzheimer’s disease.
