Owen M. O’Connor

Cell-TRACTR is a transformer-based model that segments and tracks cells in microscopy images, outperforming existing methods in tracking and division accuracy.

This study uses longitudinal single-cell chemical imaging to reveal fatty acid production heterogeneity in engineered E. coli strains over time.

DeLTA 2.0 is a deep learning tool for analyzing time-lapse microscopy data, enabling accurate segmentation and tracking of single cells in two-dimensional environments.