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Test-time augmentation-based active learning and self-training for label-efficient segmentation
However, while self-training improved the performance of single-sequence fetal body segmentation when combined with AL, it slightly deteriorated performance of multi-sequence placenta segmentation on ID data.
Automatic fetal fat quantification from MRI
It consists of two steps: 1) model-based semi-automatic fetal fat segmentations, reviewed and corrected by a radiologist; 2) automatic fetal fat segmentation using DL networks trained on the resulting annotated dataset.
Automatic linear measurements of the fetal brain on MRI with deep neural networks
Fetal MRI is increasingly used for fetal brain assessment.
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