Towards A Device-Independent Deep Learning Approach for the Automated Segmentation of Sonographic Fetal Brain Structures: A Multi-Center and Multi-Device Validation

Leveraging Clinically Relevant Biometric Constraints to Supervise a Deep Learning Model for the Accurate Caliper Placement to Obtain Sonographic Measurements of the Fetal Brain

A Multi-centre, Multi-Device Validation of a Deep Learning System for the Automated Segmentation of Fetal Brain Structures from Two-Dimensional Ultrasound Images

A Deep Learning System for the Automated Calliper Placement to Measure Multiple Fetal Brain Structures from Two-Dimensional Ultrasound Images