A Self-Supervised Learning Approach for High Throughput and High Content Cell Segmentation
V. Lam, J. M. Byers, M. Robitaille, L. Kaler, J. A. Christodoulides, M. Raphael
This paper introduces a self-supervised learning method for cell segmentation that outperforms Cellpose in accuracy and reduces reliance on labeled data and computational expertise.
bioRxiv · May 29, 2024Bioengineering