Machine learning classification and training for digital microscopy images

A system for training a neural network, the system comprising:

• one or more processors;
• and
• non-transitory computer readable storage media storing instructions that, when executed by one or more processors, cause the one or more processors to:
• receive a plurality of microscopy images of a specimen and a classification for the specimen, the plurality of microscopy images comprising a first image captured at a first magnification and a second image captured at the first magnification with a different focus than the first image;
• and
• train a machine learning model or algorithm using the plurality of images, wherein the first image and the second image are provided with one or more labels indicating the classification.

Non-transitory computer readable storage media storing instructions that, when executed by one or more processors, cause the one or more processors to:

• obtain microscopy images of a sample, wherein obtaining microscopy image comprises, for one or more regions of the sample:
• capturing a first image with a first focal plane at a first magnification;
• capturing one or more additional images with one or more additional focal planes at the first magnification;
• training a neural network using the first image and the one or more additional images, wherein a label or ground truth for the first image and the one or more additional images is the same for a same region or same specimen captured in the first image and the one or more additional images.