A four-step deep learning pipeline automatically measures five fetal brain parameters from 3D MRI, with landmark-based interpretability, achieving sub-2 mm errors on most measurements but a 4.5 mm error on corpus callosum length.
The developing human connectome project (dHCP): fetal acquisition protocol
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Towards Reliable and Reproducible Fetal Brain Biometry: A Deep Learning Approach Using MRI
A four-step deep learning pipeline automatically measures five fetal brain parameters from 3D MRI, with landmark-based interpretability, achieving sub-2 mm errors on most measurements but a 4.5 mm error on corpus callosum length.