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Research
Leveraging clinically relevant biometric constraints to supervise a deep learning model for the accurate caliper placement to obtain sonographic measurements of the fetal brain
Research
A deep learning system for the automated quantification and screening of suspected ventriculomegaly from 2D ultrasound images of the fetal brain
Research
Development and validation of an artificial intelligence based system for the automated detection of choroid plexus cyst from fetal cranial sonograms
Research
Towards a device-independent deep learning approach for the automated segmentation of sonographic fetal brain structures
Research
A Clinically-Interpretable Artificial Intelligence Based System to Automatically Detect “Lemon Sign” on Fetal Cranial Sonograms
Research
A Deep Learning System for the Automated Calliper Placement to Measure Multiple Fetal Brain Structures from Two-Dimensional Ultrasound Images
Research
A Multicentre, Multi-Device Validation of a Deep Learning System for the Automated Segmentation of Fetal Brain Structures
Research
Artificial Intelligence System (AIS) to Automatically Obtain Multiple Key Sonographic Measurements of the Fetal Brain in the Axial Views
Research
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