FreqDINO++: A Frequency-Guided Multi-Task Routing Vision Foundation Model for Universal Ultrasound Analysis

arXiv:2609.20340 · cs.CV · Submitted 2026-09-17 · Read on arXiv

cs.CV

Submitted: 2026-09-17

Updated: 2026-09-17

Code: https://github.com/MingLang-FD/FreqDINO-Plus

Terminology

• Foundation Model — 25× in this paper · explained in 3 episodes
• Adaptation — 18× in this paper · explained in 1 episode
• Transformer — 18× in this paper · explained in 2 episodes
• Generalization — 15× in this paper · explained in 13 episodes
• AUC — 13× in this paper · explained in 2 episodes
• Foundation Models — 13× in this paper · explained in 7 episodes
• Benchmark — 12× in this paper · explained in 2 episodes
• Downstream Tasks — 10× in this paper · explained in 2 episodes
• Ablation — 5× in this paper · explained in 1 episode
• Unified Framework — 5× in this paper · explained in 5 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Wavelet Transform — 4× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Computational overhead — 2× in this paper · explained in 2 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Fidelity — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Transferability — 2× in this paper · explained in 4 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Accuracy — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• AdamW Optimizer — 1× in this paper · explained in 1 episode
• Area Under the ROC Curve — 1× in this paper
• Average Surface Distance — 1× in this paper
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Dice Similarity Coefficient — 1× in this paper
• Domain Adaptation — 1× in this paper · explained in 5 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• Feature Pyramid Network — 1× in this paper
• Guided attention — 1× in this paper · explained in 2 episodes
• Hausdorff Distance — 1× in this paper
• Loss Function — 1× in this paper · explained in 2 episodes
• Matthews Correlation Coefficient — 1× in this paper
• Mean Absolute Error — 1× in this paper
• Mean Radial Error — 1× in this paper
• Parameter Efficiency — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Segmentation Masks — 1× in this paper · explained in 2 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Successful Detection Rate — 1× in this paper
• U-net architecture — 1× in this paper · explained in 3 episodes
• nnU-Net — 1× in this paper · explained in 2 episodes

Sources

• DINOv3
• Dino U-Net: Exploiting High-Fidelity Dense Features from Foundation Models for Medical Image Segmentation
• SegDINO: An Efficient Design for Medical and Natural Image Segmentation with DINO-V3
• LUMOS: Latent Universal Medical Priors for Segmentation

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