Incucyte® AI Cell Health Analysis Software Module
The Incucyte® AI Cell Health Analysis Software Module is an all-in-one analysis tool that segments cells and classifies them as live or dead. It allows users to perform cell health analyses without the need for fluorescent labels, generating accurate and objective data with reduced time requirements and cost.
Incucyte AI Cell Health Analysis Software Module Workflow
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With Incucyte® AI Cell Health Analysis Software Module and AI Label-Free Viability Assay, you can:
- Identify and segment cells to quantify live vs dead without the need for labels
- Combine with additional fluorescent indicators of cell biology for deeper insight
- Conduct real-time, robust image analysis for unbiased high-throughput compound testing
Artificial intelligence enhances label-free live-cell imaging
As cellular models are progressively increasing in complexity this has driven the need for label-free and non-perturbing approaches to accurately quantify dynamic cellular processes. The incorporation of artificial intelligence (AI) and advanced machine learning (ML) into image analysis workflows is now streamlining this process and enabling robust, user-friendly quantification of a wide range of cellular models.
This eBook provides an overview of recent label-free image analysis developments and focuses on how AI-driven image analysis is transforming live-cell imaging. This free guide will also highlight:
- How intuitive label-free analysis simplifies quantification of complex biological behavior
- The application of label-free analysis in the drug discovery process through providing high-throughput physiologically relevant insights into cell health and compound efficacy
AI-driven label-free quantification of cell viability using live-cell analysis
Live-cell imaging enables acquisition of phase contrast images and provides an ideal platform to study multi-faceted biological paradigms in drug discovery. This is vital to our understanding of human diseases and treatment strategies. In this application note, Sartorius describes an automated, robust solution for label-free cell segmentation and live/dead classification of individual cells using integrated AI-based software. The Incucyte® AI Cell Health Analysis Software Module, driven by trained convolutional neural networks (CNN), allows for reliable monitoring of cell viability in a non-perturbing unbiased manner with minimal user input. Here, Sartorius shows validation of the analysis software across a wide range of live and dead adherent and non-adherent cell types and exemplifies how this approach can provide high-throughput, physiologically relevant insights into cell health through accurately predicting cell death across multiple treatments.
