Artificial Intelligence Brings Specificity to Label-Free Imaging for Assisted Reproduction

As part of a project to develop specific traits in cattle that would make them resistant to heat and diseases in tropical regions, researchers at the University of Illinois at Urbana-Champaign developed a phase-imaging technique to determine which sperm samples would work best for in vitro fertilization. This technique is being further developed for humans. The approach combines label-free imaging and artificial intelligence to obtain nondestructive markers for reproductive outcomes. The phase-imaging system shows nanoscale morphological details from unlabeled cells, while deep learning provides a structural specificity map for segmenting with high accuracy the head, midpiece, and tail of the sperm. “We knew from the...