Label-Free Cell Nuclei Analysis with AI
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Automated analysis of cell populations in microwell plates, without the need for fluo-rescent labeling, offers researchers a number of significant benefits. For the process to be reliable, however, it is essential that proto-cols are both robust and easy to use. Meth-ods based on artificial intelligence (AI) are ideally suited to address this challenge. Using the right software, AI-based image analysis requires minimal human input and a short training phase. Here, we demonstrate as an example application for the new self-learn-ing microscopy approach how AI can reliably detect and analyze cell nuclei from unstained brightfield images with an accuracy that ex-ceeds fluorescence-based methods.
Read full application note here.