Utilization of convolutional neural networks to analyze microscopic images for high-throughput screening of mesenchymal stem cells
MuYun Liu,
XiangXi Du,
JunYuan Hu
et al.
Abstract:This work investigated the high-throughput classification performance of microscopic images of mesenchymal stem cells (MSCs) using a hyperspectral imaging-based separable convolutional neural network (CNN) (H-SCNN) model. Human bone marrow mesenchymal stem cells (hBMSCs) were cultured, and microscopic images were acquired using a fully automated microscope. Flow cytometry (FCT) was employed for functional classification. Subsequently, the H-SCNN model was established. The hyperspectral microscopic (HSM) images… Show more
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