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We present the first system that provides real-time probe movement guidancefor acquiring standard planes in routine freehand obstetric ultrasoundscanning. Such a system can contribute to the worldwide deployment of obstetricultrasound scanning by lowering the required level of operator expertise. Thesystem employs an artificial neural network that receives the ultrasound videosignal and the motion signal of an inertial measurement unit (IMU) that isattached to the probe, and predicts a guidance signal. The network termedUS-GuideNet predicts either the movement towards the standard plane position(goal prediction), or the next movement that an expert sonographer wouldperform (action prediction). While existing models for other ultrasoundapplications are trained with simulations or phantoms, we train our model withreal-world ultrasound video and probe motion data from 464 routine clinicalscans by 17 accredited sonographers. Evaluations for 3 standard plane typesshow that the model provides a useful guidance signal with an accuracy of 88.8%for goal prediction and 90.9% for action prediction.

Automatic Probe Movement Guidance for Freehand Obstetric Ultrasound