Method for classifying cells

Abstract

The disclosure provides example embodiments for automatically or semi-automatically classifying cells in microscopic images of biological samples. These embodiments include methods for selecting training sets for the development of classifier models. The disclosed selection embodiments can allow for the re-training of classifier models using training examples that have been subjected to the same or similar incubation conditions as target samples. These selection embodiments can reduce the amount of human effort required to specify the training examples. The disclosed embodiments also include the classification of individual cells based on metrics determined for the cells using phase contrast imagery and defocused brightfield imagery. These metrics can include size, shape, texture, and intensity-based metrics. These metrics are determined based on segmentation of the underlying imagery. The segmentation is based, in some embodiments, on phase contrast imagery and/or defocused brightfield imagery of biological samples.