Pre-Clinical Validation of an AI-Powered Automated Robotic Intracytoplasmic Sperm Injection System

Conference Papers
Written By C22 Admin

Hernandez et al., American Society for Reproductive Medicine (ASRM) 2025 Scientific Congress & Expo

ICSI success depends on an embryologist's ability to select sperm, position the egg correctly, and inject without causing damage, contributing to outcome variability among operators.

This study tested an AI-powered system that automates all critical ICSI steps, from sperm selection through injection, using computer vision and machine learning. The system was rigorously evaluated using animal models to establish safety protocols and optimize performance parameters before any human application.

The automated system achieved 94% survival rates in hamster oocytes injected with human sperm, matching manual controls, while meeting or exceeding all predefined performance criteria for precision and timing. The AI consistently selected morphologically optimal sperm and executed injections with precision.

This pre-clinical validation establishes the foundation for potentially eliminating operator-dependent variability in ICSI.

 
C22 Admin
Previous

Real-Time Automated Detection of Human Cumulus-Oocyte Complexes Using High-Resolution Imaging and AI Inference
Next

Advancing ICSI Robotics: Follow-Up on the Transition from Remote to Fully Automated Intracytoplasmic Sperm Injection