A SqueezeNet CNN classifies immune cells from label-free multiphoton autofluorescence images, achieving 0.89 ROC-AUC for binary classification and 0.689 F1 for six-class tasks.
Different cell imaging methods did not significantly improve immune cell image classification performance
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Detecting immune cells with label-free two-photon autofluorescence and deep learning
A SqueezeNet CNN classifies immune cells from label-free multiphoton autofluorescence images, achieving 0.89 ROC-AUC for binary classification and 0.689 F1 for six-class tasks.