In this episode, learn how AI-powered segmentation, spatial analysis, and phenotyping can help you gain new insights for 3D images with complex morphological measurements featuring up to 15 biomarkers.
See how to characterize tissue microenvironments and examine the differences between normal and disease tissues without the need to code or train Deep Learning models—all with Aivia.
Plus, get your 3D spatial biology results faster with an inbuilt, enhanced Deep Learning model that can accurately detect and partition cells with morphological variations.
You will discover how to leverage your expertise or simple automation to classify cells into different phenotypes and interactively explore them in their spatial context.
We also demonstrate how, with a few clicks, you can produce key measurements such as percentage distribution, Pearson correlation coefficient, and dimensionality reduction. You will also learn how to visualize the relationship between biomarkers and clusters using dendrograms.
Watch the full presentation here: https://microscopyfocus.com/enhancing-3d-spatial-biology-with-ai-simplified-insights-for-all/
Browse all episodes of the Listen In Series here: https://listen-in.bitesizebio.com/
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