Single-cell dispensing for automated cell isolation of individual cells has gained increased attention in the biopharmaceutical industry, mainly for production of clonal cell lines. Here, machine learning for classification of cell images is applied for 'real-time' cell viability sorting on a single-cell printer. We show that an extremely shallow convolutional neural network (CNN) for classification of low-complexity cell images outperforms more complex architectures.
View Article and Find Full Text PDFThe handling of single cells is of great importance in applications such as cell line development or single-cell analysis, e.g., for cancer research or for emerging diagnostic methods.
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