UltraBench 2: Towards Robust Evaluation of Vision Foundation Models on Ultrasound

arXiv:2609.28610 · cs.CV, cs.LG · Submitted 2026-09-23 · Read on arXiv

cs.CV, cs.LG

Submitted: 2026-09-23

Updated: 2026-09-23

Code: https://github.com/adamtupper/ultrabench2

Project page: https://gbc-iitd.github.io/data/gbcu

Terminology

• Benchmark — 56× in this paper · explained in 2 episodes
• Fine-Tuning — 27× in this paper · explained in 5 episodes
• Foundation Model — 25× in this paper · explained in 3 episodes
• Foundation Models — 21× in this paper · explained in 7 episodes
• Transformer — 12× in this paper · explained in 2 episodes
• F1 Score — 6× in this paper · explained in 3 episodes
• Segmentation Masks — 6× in this paper · explained in 2 episodes
• Distillation — 4× in this paper · explained in 2 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 3 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Linear Probing — 2× in this paper · explained in 2 episodes
• Segment Anything Model — 2× in this paper
• Self-Supervised Learning — 2× in this paper · explained in 7 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Guided attention — 1× in this paper · explained in 2 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Masked Autoencoder (MAE) — 1× in this paper · explained in 5 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• alpha — 1× in this paper · explained in 1 episode

Sources

• The Benchmark Lottery
• Pretext Matters: An Empirical Study of SSL Methods in Medical Imaging
• Segment Anything
• Mapping global dynamics of benchmark creation and saturation in artificial intelligence
• GEO-Bench-2: From Performance to Capability, Rethinking Evaluation in Geospatial AI
• DINOv3
• A Fully Open and Generalizable Foundation Model for Ultrasound Clinical Applications
• OpenUS: A Fully Open-Source Foundation Model for Ultrasound Image Analysis via Self-Adaptive Masked Contrastive Learning
• MMOTU: A Multi-Modality Ovarian Tumor Ultrasound Image Dataset for Unsupervised Cross-Domain Semantic Segmentation

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