Convolutional neural networks that teach microscopes how to image

Understand

Deep learning algorithms offer a powerful means to automatically analyze the content of medical images.

• However, many biological samples of interest are primarily transparent to visible light and contain features that are difficult to resolve with a standard optical microscope.
• Here, we use a convolutional neural network (CNN) not only to classify images, but also to optimize the physical layout of the imaging device itself.
• We increase the classification accuracy of a microscope's recorded images by merging an optical model of image formation into the pipeline of a CNN.