Imaging and quantitatively analyzing organoids at scale remains challenging because conventional microscopy workflows are time intensive, while alternative methods may sacrifice spatial information or limit throughput. Advances in high-content imaging and automated image analysis are helping researchers generate reproducible phenotypic data across larger sample sets while reducing manual bias.
This application note outlines a high-throughput workflow for imaging and analyzing human intestinal organoid (HIO) monolayers, highlighting approaches for automated image acquisition, whole-well reconstruction, and quantitative phenotypic analysis using open-source image analysis tools.
Download this application note to learn:
- How automated imaging improves throughput and phenotypic reproducibility
- Methods for whole-well image reconstruction and quantitative analysis
- Strategies for scalable HIO phenotyping using automated image analysis
