Medical Image Segmentation with Domain Adaptation: A Survey

Understand

Deep learning (DL) has shown remarkable success in various medical imaging data analysis applications.

• However, it remains challenging for DL models to achieve good generalization, especially when the training and testing datasets are collected at sites with different scanners, due to domain shift caused by differences in data distributions.
• Domain adaptation has emerged as an effective means to address this challenge by mitigating domain gaps in medical imaging applications.
• In this review, we specifically focus on domain adaptation approaches for DL-based medical image segmentation.