An nnU-Net segmentation model produces IVIM parameters statistically indistinguishable from manual segmentations, and a total-lung-volume classifier separates FGR from controls with 100% accuracy on a 6-case test set, though with low statistical power.
Prenatal Diagnosis42(5), 628–635 (2022)
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Deep Learning-Based Fetal Lung Segmentation from Diffusion-weighted MRI Images and Lung Maturity Evaluation for Fetal Growth Restriction
An nnU-Net segmentation model produces IVIM parameters statistically indistinguishable from manual segmentations, and a total-lung-volume classifier separates FGR from controls with 100% accuracy on a 6-case test set, though with low statistical power.