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.
Automatic ventriculomegaly detection in fetal brain MRI: a step-by-step deep learning model for novel 2D–3D linear measurements
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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.