AI-Enabled Label-Free Detection for Advanced Cell Analysis
Smarter Imaging Without Fluorescent Labels
Traditional fluorescence-based imaging workflows can increase complexity, cost, and processing time. Discover how AI-powered label-free detection with IN Carta® Image Analysis Software enables accurate, scalable, and non-invasive cell analysis using transmitted light imaging alone.
The ImageXpress® HCS.ai High-Content Screening System delivers exceptional imaging performance and intelligent analysis capabilities designed specifically for complex 3D workflows.
Key Benefits
- Achieve over 97% nuclei detection accuracy using transmitted light images
- Eliminate the need for fluorescent or chemical labels
- Preserve live cells for real-time monitoring and kinetic studies
- Reduce reagent costs and streamline imaging workflows
- Train customizable AI models across multiple cell lines
- Generate accurate dose-response data with strong correlation to traditional methods
Why Researchers Are Interested
This application note demonstrates how AI-enabled segmentation models within IN Carta® Image Analysis Software accurately detect nuclei and cells using label-free transmitted light images.
Researchers successfully:
- Built customizable AI segmentation models using SINAP
- Achieved high detection accuracy across multiple cell lines
- Compared label-free results against DAPI-based ground truth
- Generated reliable dose-response curves for anti-cancer compounds
- Reduced workflow complexity while maintaining analytical accuracy
The result is a faster, scalable, and more efficient approach to high-throughput cell analysis and phenotypic screening.
Download the Application Note
Learn how AI-driven label-free imaging can improve cell analysis workflows, accelerate screening applications, and enable deeper biological insights.