A Survey on Domain Generalization for Medical Image Analysis

Understand

Medical Image Analysis (MedIA) has emerged as a crucial tool in computer-aided diagnosis systems, particularly with the advancement of deep learning (DL) in recent years.

• However, well-trained deep models often experience significant performance degradation when deployed in different medical sites, modalities, and sequences, known as a domain shift issue.
• In light of this, Domain Generalization (DG) for MedIA aims to address the domain shift challenge by generalizing effectively and performing robustly across unknown data distributions.
• This paper presents the a comprehensive review of substantial developments in this area.