A training-free prototype memory-guided framework for multi-class prenatal ultrasound anomaly classification and localization using few reference images per class, validated on a 9-category multi-center dataset.
In: arxiv:2509.06467 (2026)
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
representative citing papers
MaRS improves reconstruction-based OOD detection by replacing L2 residual norms with variance-aware Mahalanobis scoring on autoencoder outputs.
Frozen ViT embeddings in chest radiography suppress small-lesion signal at the CLS token but recover it via patch-local pooling on the same forward pass across multiple models and large cohorts.
ORACLE-CT improves CT classification performance by using anatomy-specific support pooling based on multi-organ segmentation, showing gains in AUROC on internal and external datasets.
DINOv3 at 512x512 resolution with ConvNeXt-B outperforms prior initializations for adult chest X-ray classification but shows no benefit in pediatric cohorts or at 1024 resolution.
Large-scale real-world study demonstrates that bottlenecking pre-trained ViT encoders to a scalar per patch produces interpretable affordance features useful for navigation policies.
citing papers explorer
-
Resolution scaling governs DINOv3 transfer performance in chest radiograph classification
DINOv3 at 512x512 resolution with ConvNeXt-B outperforms prior initializations for adult chest X-ray classification but shows no benefit in pediatric cohorts or at 1024 resolution.