System and method for label-free identification and classification of biological samples

Abstract

A system and method of analyzing a biological sample using an imaging system are disclosed. An image acquisition module instructs the imaging system to obtain a label free image of a training biological sample and in response receives a first training image. The image acquisition module also instructs the imaging system to cause the training biological sample to fluoresce and obtain an image of the training biological sample undergoing fluorescence, and in response receives a second training image. An analysis module analyzing the second training image to generate a plurality of training cell characteristics, wherein each of the plurality training cell characteristics is associated with one of a plurality of training cells that comprise the training biological sample. A training module trains a machine learning system using the first training image and the plurality of training cell characteristics to develop a trained machine learning system such that when the trained machine learning system is operated with the first training image as an input, the trained machine learning system generates a plurality of predicted cell characteristics that correspond to the plurality of training cell characteristics.