1. A method comprising: obtaining input data comprising a plurality of images of one or more biological cells, wherein each image is an image of the one or more biological cells illuminated with a respective optical microscopy technique of a plurality of different optical microscopy techniques, wherein the plurality of different optical microscopy techniques include at least one of differential interference contrast microscopy or foveated imaging; processing the input data using a stained cell neural network, wherein the stained cell neural network has been configured through training to receive the input data comprising the plurality of images of the one or more biological cells and to process the input data to perform fully convolutional image-to-image regression from the input data to one or more stained cell images, wherein each stained cell image depicts a respective stained version of the one or more biological cells in the input data; and processing the one or more stained cell images generated by the stained cell neural network using a cell characteristic neural network, wherein the cell characteristic neural network has been configured through training to receive the one or more stained cell images and to process the one or more stained cell images to generate a cell characteristic output that characterizes features of the biological cells that are stained in the one or more stained cell images.