Back

Automated Image-Based Cell Sorting by Targeted Photopolymerization

Maurer, S. J.; Abele, T.; Stange, S. R.; Hoffmann, K. H.; Poschke, I.; Platten, M.; Göpfrich, K.

2025-12-27 cell biology
10.64898/2025.12.27.693999 bioRxiv
Show abstract

We present an automated image-based cell sorting method capable of a through-put of hundreds of cells per second. Our microscopy platform integrates automated image acquisition, machine-learning based classification and sub-sequent depletion of up to 99.98 % of negative cells by spatially controlled photo-encapsulation, preserving target cells for collection. Applied to peripheral blood mononuclear cells, the method achieves the label-free, morphology-based enrichment of activated T cells for downstream applications in biomedicine.

Matching journals

The top 8 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.