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AI-based analysis of complex biological phenotypes

While high-content imaging is an efficient tool to capture phenotypic changes in complex cell morphology, quantitative image analysis is still a challenging task, due to multiple complex readouts, manifold changes in cell morphology, and the complexity of analysis algorithms used.

Machine learning (AI)-based image analysis can address these challenges by reducing the effort and expertise required to capture and analyze morphological changes.

In this poster, we demonstrate a workflow, which integrates the ImageXpress® Micro Confocal system with ViQi’s AI platform to quantify complex biological phenotypes.

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