An AI-based Approach to High-Content Phenotypic Characterization of Human iPSC-Derived Neuronal Cells
While high-content imaging is an efficient tool to capture phenotypic changes in neurite morphology, quantitative image analysis is still a challenging task, due to the manifold changes in morphology and the complexity of analysis algorithms used. Deep learning (AI)-based image analysis can address these challenges by reducing the effort and expertise required to capture morphological changes.
In this webinar, we demonstrate a workflow, which integrates the ImageXpress® system with the Ai-based Genedata Imagence® platform to analyze neurotoxicity in human iPSC-derived neurons.
- Screening of neurotoxicity and neurite outgrowth assays using the ImageXpress Micro Confocal system
- Overview of fully integrated imaging and analysis workflow
- Software Demo of the Gendata Imagence workflow
- Quantification of neurotoxicity using Genedata Imagence
Oksana Sirenko, PhD, Senior Research Scientist, Molecular Devices
Matthias Fassler, PhD, Scientific Account Manager, Genedata