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Nguyen Lan Vi Vu

2 accepted papers

2026

ALIGNING WHAT YOU SEPARATE: DENOISED PATCH MIXING FOR SOURCE-FREE DOMAIN ADAPTATION IN MEDICAL IMAGE SEGMENTATION

ICASSP 2026poster

Source-Free Domain Adaptation (SFDA) is emerging as a compelling solution for medical image segmentation under privacy constraints, yet current approaches often ignore sample difficulty and struggle with noisy supervision under domain shift. We present a new SFDA framework that leverages Hard Sample…

Cited by 0SourcePDFScholar
2026

DOMAIN-INVARIANT MIXED-DOMAIN SEMI-SUPERVISED MEDICAL IMAGE SEGMENTATION WITH CLUSTERED MAXIMUM MEAN DISCREPANCY ALIGNMENT

ICASSP 2026poster

Deep learning has shown remarkable progress in medical image semantic segmentation, yet its success heavily depends on large-scale expert annotations and consistent data distributions. In practice, annotations are scarce, and images are collected from multiple scanners or centers, leading to mixed-d…

Cited by 0SourcePDFScholar