Domain Adaptation for Medical Image Analysis: A Survey

Machine learning techniques used in computer-aided medical image analysis usually suffer from the domain shift problem caused by different distributions between source/reference data and target data. We also provide a brief summary of the benchmark medical image datasets that support current domain adaptation research.

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• 1 As a promising solution, domain adaptation has attracted considerable attention in recent years.
• 2 The aim of this paper is to survey the recent advances of domain adaptation methods in medical image analysis.
• 3 We first present the motivation of introducing domain adaptation techniques to tackle domain heterogeneity issues for medical image analysis.

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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