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University of Nottingham Ningbo China
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This work proposes FreqDINO++, a frequency-guided multi-task routing vision foundation model for universal ultrasound analysis and demonstrates that FreqDINO++ consistently outperforms strong baselines and recent foundation models across 27 diverse clinical task scenarios, while also showing promising generalization to unseen data.
ViaMOBO reveals that understanding variable interactions can drastically enhance optimization efficiency in high-dimensional spaces, outperforming traditional methods.
Uncertainty-aware segmentation can drastically improve performance in medical imaging, with DistMedVL achieving superior results using only 6.3M parameters.
