OBJECTIVE
Transferring large-scale medical foundation models to specific clinical tasks remains challenging, particularly in multi-center scenarios with heterogeneous data distributions and privacy constraints. Existing adaptation strategies provide limited solutions for collaboratively adapting foundation models acros...
Xin-Ran Wu, Ren-Cheng Zheng, Yu-Xiang Dai et al.· IEEE transactions on bio-med...· 0 citations
A fully automatic, multi-task learning framework for LA strain quantification, validated in multi-center two-vendor data, enhances tracking accuracy and speed over prior methods, enabling rapid, scalable atrial function assessment in routine care.
Yi-Chen Zhao, Haiyang Chen, Yiwen Gong et al.· Journal of Cardiovascular Ma...· 0 citations
Results indicate that DMFT provides a promising framework for accurate and efficient cardiac MRIreconstruction, and structure aware prior guidance offers additional interpretability support in Healthcare 4.0 scenarios.
Jun Lyu, Bo Zhao, Selwa A. F. Al-Hazzaa et al.· IEEE journal of biomedical a...· 0 citations
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