High-throughput cellular imagers
Cell3iMager systems are 3D cell culture scanners and cell morphology analysis systems developed by SCREEN that are able to perform high-speed measurement and analysis of the multiplication and morphological changes in cells without using any test reagent. The devices use proprietary image processing technologies that allow faster image capture, measurement and data analysis, and are compatible with all major 3D cell culture platforms.
Cell3iMager is a simple, high-throughput, bright field scanner designed specifically to simplify and accelerate quantitative and qualitative measurement of 3D spheroids. This unique LED-based imaging system allows the user to identify and measure single or multiple spheroids per well in a microplate rapidly and automatically. The companion 3D optimized analysis software allows faster image capture, measurement and data analysis, and is compatible with all major 3D cell culture platforms. To fit varying budgets and throughput needs, the imager is available in two models: the single-plate Cell3iMager neo (cc-3000) or the four-plate Cell3iMager (cc-5000).
Cell3iMager duos is a benchtop imager capable of high-throughput, whole-well imaging at high-resolution, and provides both bright-field and fluorescence imaging options. It can be used as a valuable tool in several drug discovery and development applications as well as toxicology testing to select therapeutic targets and treatment strategies before costly and tedious testing in animal models. Cell3iMager duos facilitate uniform, whole-well imaging of each and every cell in a well, including well periphery, at high-resolutions. Duos proprietary lens captures images at two different resolutions, 0.8 µm & 4.0 µm, thus enable qualitative and quantitative measurement of single cells and colonies grown in 2D culture as well as growth and morphological changes of spheroids/organoids grown in 3D culture. Duos automatic cell morphological classification (ACMC) feature allows ‘intelligent’ automatic classification of live and dead spheroids/cells, using logic derived from a user-defined reference set of respective objects.