FLMMIF: privacy-preserving federated multi-modal medical image fusion
As a pivotal technique in smart healthcare, medical image fusion integrates complementary functional and structural information to facilitate accurate diagnosis and enhance clinical decision-making reliability. However, existing centralized methods typically raise serious data privacy concerns, while standard distributed approaches often fail to balance global generalization with local node personalization due to data heterogeneity. To address this, we propose FLMMIF, a privacy-preserving framew
Record details
Published: 14 July 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Privacy · Healthcare
Retrieved: 14 July 2026
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ethics.ai (14 July 2026), “FLMMIF: privacy-preserving federated multi-modal medical image fusion,” evidence record 2185, https://ethics.ai/record/2185 (originally published by Frontiers in Artificial Intelligence).
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