Classification workflow for flexible image based particle sorting

An apparatus comprising:

• a non-transitory memory for storing an application, the application for:
• pre-training a feature encoder using cell images;
• performing unsupervised clustering to identify populations, wherein the unsupervised clustering receives output from pre-training the feature encoder, wherein performing the unsupervised clustering includes classifying cells of the cell images into clusters, wherein a user labels the clusters after the unsupervised clustering based on viewing the cluster and representative information, wherein clusters are labeled as “sort” or “do not sort;”
• implementing a classifier to fine-tune supervised classification;
• and
• performing real-time classification of cells during active sorting using the classifier, wherein the real-time classification processes an entire image of each cell;
• and
• a processor coupled to the memory, the processor configured for processing the application.

A system comprising:

• a first device configured for acquiring cell images;
• and
• a second device configured for:
• pre-training a feature encoder using the cell images;
• performing unsupervised clustering to identify populations, wherein the unsupervised clustering receives output from pre-training the feature encoder, wherein performing the unsupervised clustering includes classifying cells of the cell images into clusters, wherein a user labels the clusters after the unsupervised clustering based on viewing the cluster and representative information, wherein clusters are labeled as “sort” or “do not sort;”
• implementing a classifier to fine-tune supervised classification;
• and
• performing real-time classification of cells during active sorting using the classifier, wherein the real-time classification processes an entire image of each cell.