Shifting Adaptation from Weight Space to Memory Space: A Memory-Augmented Agent for Medical Image Segmentation
MemSeg-Agent proposes shifting medical image segmentation adaptation from updating model weights to updating lightweight memory units. This agent uses static, few-shot, and test-time working memories managed by an AI controller. It enables few-shot learning, federated supervised learning, and online adaptation for domain shift without retraining the large backbone.