FetSelect pairs a frozen vision foundation model with a hybrid multi-head design and BYOL pretraining on ultrasound data to select quality fetal frames, reporting mean AUROC 0.956 on expert-labeled test data.
Scientific Data11(1), 436 (2024)
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FetSelect: Task-Specific Architectures and Self-Supervised Learning for Automated Fetal Ultrasound Frame Selection
FetSelect pairs a frozen vision foundation model with a hybrid multi-head design and BYOL pretraining on ultrasound data to select quality fetal frames, reporting mean AUROC 0.956 on expert-labeled test data.