Easy-to-use image analysis software enables single cell quantitation of cell types and division rates in complex 3D tissues including living Drosophila brains, mouse embryos and Zebrafish organoids.

A novel phenotypic screening platform based on immunofluorescent imaging of histone modifications enables accurate identification of cell fates and environmental perturbations.

Image3C is a new image-based analysis of cell population composition for research organisms in which detailed cellular phenotypes are unknown or for which species-specific reagents are not available.

The presented primary epithelial acinus-based platform for studying interactions between normal and malignant cells will enable in depth analysis of the tumor initiation process on a molecular level.

In the Arabidopsis ovule primordium, germinal fate plasticity is coupled to the morphogenetic processes shaping the organ.

A computational strategy for extracting representative numerical features from 3D microscopy data enables in-depth quantitative analysis of cell and tissue organization through machine learning-driven data integration and context-guided visualization.

MotionTracking is freely available software that can generate multi-scale geometrical models of mammalian tissue and perform quantitative analysis of tissue architecture.

The application of deep learning fills a major gap in host–pathogen research providing for unbiased, multi-module high-throughput image analysis.

Machine learning in conjunction with super-resolution imaging allows for the first time to quantitatively analyse large and heterogenous virus samples structure at a high throughput and specificity.

New reconstruction methods are used to create a publicly available dense reconstruction of the neurons and chemical synapses of central brain of Drosophila, with analysis of its graph properties.