Approximately 99% of maternal deaths - those related to pregnancy or birth complications - occur in low-resource settings where the ability to diagnose and manage pregnancy complications is limited. Prenatal ultrasound screening is used routinely in wealthier countries around the world and is recommended by the World Health Organization. However, the cost of ultrasound equipment and trained sonographers is prohibitive in many regions of the world.
The BabyChecker project develops Artificial Intelligence (AI) tools which work in combination with low-cost ultrasound devices. These ultrasound devices connect directly with a smartphone running the babychecker AI software so that the entire imaging and interpretation process can be run offline and at low-cost. The image acquisition can be done by an operator with minimal training, following a standard protocol. The babychecker AI software will perform standard prenatal checks to determine the gestational age and position of the baby and the presence of more than one fetus, for example. In this way, high risk pregnancies can be identified and managed at local healthcare facilities.
This research project is funded by Delft Imaging.