Researchers have unveiled a major step forward in artificial intelligence–driven maternal and fetal healthcare with the release of the Intrapartum Ultrasound Grand Challenge (IUGC) benchmark and its accompanying large-scale dataset. The study introduces a clinically oriented multi-task framework that integrates standard plane classification, fetal head–pubic symphysis segmentation, and automatic biometry measurement from ultrasound videos, enabling more accurate and reliable monitoring of labor progression.
The IUGC initiative addresses a critical global health challenge: nearly 45% of maternal and neonatal deaths and stillbirths occur during the intrapartum phase, with a disproportionate burden in low- and middle-income countries. By leveraging deep learning, the proposed framework aims to reduce reliance on highly trained sonographers and expand access to high-quality intrapartum ultrasound assessment in resource-limited settings.
A key highlight of the project is the release of the largest multi-center intrapartum ultrasound video dataset to date, comprising 774 videos and over 68,000 annotated frames collected from three hospitals. This diverse dataset captures real-world variability in anatomy, imaging devices, and acquisition conditions, providing a robust foundation for training and benchmarking next-generation AI models.
A key highlight of the project is the release of the largest multi-center intrapartum ultrasound video dataset to date, comprising 774 videos and over 68,000 annotated frames collected from three hospitals. This diverse dataset captures real-world variability in anatomy, imaging devices, and acquisition conditions, providing a robust foundation for training and benchmarking next-generation AI models.
All benchmark results, evaluation tools, and datasets have been publicly released to promote reproducible research and accelerate innovation. This open-science initiative is expected to drive continued progress toward safe, scalable, and AI-assisted intrapartum ultrasound biometry, ultimately improving outcomes for mothers and newborns worldwide.