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Automated Interpretation of Blood Culture Gram Stains by Use of a Deep Convolutional Neural Network
2017
Journal of Clinical Microbiology
Microscopic interpretation of stained smears is one of the most operator-dependent and time-intensive activities in the clinical microbiology laboratory. Here, we investigated application of an automated image acquisition and convolutional neural network (CNN)-based approach for automated Gram stain classification. Using an automated microscopy platform, uncoverslipped slides were scanned with a 40× dry objective, generating images of sufficient resolution for interpretation. We collected
doi:10.1128/jcm.01521-17
pmid:29187563
pmcid:PMC5824030
fatcat:h7ey57wcxvhzxivl3fitxgct2y