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Hierarchical variants of so‐called deep convolutional neural networks (DCNNs) have facilitated breakthrough results for numerous pattern recognition tasks in recent years. We assess the potential of these novel whole‐image classifiers for Raman‐microscopy‐based cytopathology. Conceptually, DCNNs facilitate a flexible combination of spectral and spatial information for classifying cellular images as...
The image displays the construction of the first layers of a deep convolutional neural network for classifying Raman microscopic images of urotheleal cells as either cancerous or normal. The input layer is obtained by the intensity images of two selected wavenumbers, indicated as red and green, respectively. Deeper layers are constructed by convolution operations indicated in the yellow box. The final...
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