The rapid and accurate identification and classification of cell types is of great significance in scientific research and clinical diagnosis. We proposed the wide-field hyperspectral interferometry rapid label-free (WHIRL)imaging method. Hyperspectral imaging collects and processes information from across the electromagnetic spectrum. In machine learning, support-vector machine (SVM) is one of most commonly used supervised learning models. We cultured a variety of cells and performed hyperspectral imaging by spot scanning with a spectrometer. Then use the SVM method for classification. The accuracy of distinguishing benign from malignant is >99%, and the accuracy of distinguishing different lung cancer subtypes is >90%,which indicates a promising prospect for cell identification and classification based on WHIRL imaging method.
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