Analyzing the cell cycle is crucial for understanding proliferation and disease. While high-throughput methods sacrifice spatial information, Cytely enables rapid classification of cell cycle stages using only a nuclear stain and morphological profiling, preserving spatial context and enabling reproducible quantification.

Smart microscopy is transforming life sciences by automating experimental imaging workflows and enabling real-time adaptation based on feedback from images and other data streams. This shift increases throughput, improves reproducibility, and expands the functional capabilities of microscopes

Analyzing cell populations in whole blood is a fundamental yet challenging task. Even after standard preparation steps, samples often contain mixed populations of leukocytes, platelets, and red blood cells (RBCs). Cytely enables researchers to rapidly identify and quantify these populations at the single-cell level. Through scatter plots and intuitive gating, different blood cell types can be distinguished and characterized in an unbiased, interactive workflow. Key features demonstrated in this note: Visualizing heterogeneity across a mixed cell population Identifying populations (neutrophils, platelets, RBCs) using scatter plots Gating to isolate neutrophil subsets

In microscopy, the transition from qualitative observation to quantitative data is a significant challenge. Manual analysis is susceptible to user bias and is impractical for large datasets, while many automated solutions can obscure the connection between the quantitative data and the original visual context. Cytely is a web-based tool designed to address these challenges by integrating automated image segmentation with interactive data exploration. It provides a structured workflow for deriving quantitative metrics from cell populations and linking those metrics back to their source images in real-time.