Real-Time Automated Detection of Human Cumulus-Oocyte Complexes Using High-Resolution Imaging and AI Inference
Mendizabal-Ruiz et al., 2025
Identifying and collecting eggs from follicular fluid after retrieval is a time-sensitive process requiring experienced embryologists to quickly identify the eggs (in jargon called “cumulus-oocyte complexes”). Missing even a single egg can significantly impact a patient's treatment outcome.
Here, the authors describe an automated system for egg finding which combines 20-megapixel imaging with artificial intelligence to automatically detect eggs in a dish following egg collection. The AI correctly identified 93% of eggs in clinical samples, providing real-time detection that could serve as a critical safety net during egg collection procedures.
This technology represents a significant advance in laboratory automation, offering immediate practical benefits for improving egg recovery rates while paving the way for fully automated oocyte identification systems.