Notas de aplicação
Label-free cell counting using AI-driven fully automated smart imaging system ECLIPSE Ji
setembro 2023
ECLIPSE Ji with Smart Experiment software enables seamless experiments from image acquisition to analysis and graph creation. Pre-trained Artificial Intelligence (AI) and pre-defined imaging processes automatically optimize image acquisition and analysis condition settings, providing visualized data and cell count information with simple operation. This application note introduces an example of using Cell Counting – endpoint module of Smart Experiments, to detect cell nucleus regions from brightfield images using AI. This can be accomplished label-free, and measures the total number of cell nuclei in a given sample.
Keywords: cell counting, label-free, AI, pre-trained AI, automation
Experimental overview
- HeLa cells were seeded in 24-well plates and cultured for 24 hours.
- The well plate was placed on ECLIPSE Ji and image acquisition and analysis was run automatically by selecting the Cell Counting – endpoint icon.
Table. 1: Detection regions, fluorescence labels, and image acquisition conditions
Results
Fig. 1:Brightfield and binarized images of HeLa cells
2x2 tiling image, (A) brightfield image, (B) nuclear mask overlaid on brightfield image.
Product information
Smart Imaging System ECLIPSE Ji
ECLIPSE Ji is an AI-Driven, fully automated imaging system. By using it in combination with NIS-Elements SE, image acquisition, analysis, and graph creation can be run seamlessly and automatically. It is equipped with "CellFinder.ai“, which uses AI to find the optimal focal plane in autofocus settings that normally require advanced human judgment. Various trained AIs are implemented in the image acquisition and analysis process. This greatly reduces the number of steps for setting and optimization and makes it easier for everyone to get results.
Imaging Software NIS-Elements SE
SmartExperiment Basic Set
Cell Counting - endpoint
- Fully automated from image acquisition to analysis and graph display.
- Label-free cell counting by pre-trained AI