PolarMAE is a new unsupervised pre-training method for fetal ultrasound that uses progressive visual-semantic screening, acoustic-bounded constraints, and polar-texture masking to reach state-of-the-art performance on downstream interpretation tasks.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.CV 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
PaCX-MAE augments masked autoencoding of chest X-rays with dual contrastive-predictive alignment to ECG and laboratory embeddings, reporting gains on physiology-dependent tasks while remaining unimodal at test time.
citing papers explorer
-
PolarMAE: Efficient Fetal Ultrasound Pre-training via Semantic Screening and Polar-Guided Masking
PolarMAE is a new unsupervised pre-training method for fetal ultrasound that uses progressive visual-semantic screening, acoustic-bounded constraints, and polar-texture masking to reach state-of-the-art performance on downstream interpretation tasks.
-
PaCX-MAE: Physiology-Augmented Chest X-Ray Masked Autoencoder
PaCX-MAE augments masked autoencoding of chest X-rays with dual contrastive-predictive alignment to ECG and laboratory embeddings, reporting gains on physiology-dependent tasks while remaining unimodal at test time.