The practical implementation of deep neural networks in clinical settings faces hurdles due to variations in data distribution across different centers. While the incorporation of query-guided Transformer has improved performance across diverse tasks, the full scope of their generalization capabilities remains unexplored. Given the ability of the query-guided Transformer to dynamically adjust to individual samples, fulfilling the need for domain generalization, this paper explores the potential of query-based Transformer for cross-center genera...
