Q-Net: Query-Informed Few-Shot Medical Image Segmentation. (arXiv:2208.11451v1 [cs.CV])

Deep learning has achieved tremendous success in computer vision, while
medical image segmentation (MIS) remains a challenge, due to the scarcity of
data annotations. Meta-learning techniques for few-shot segmentation (Meta-FSS)
have been widely used to tackle this challenge, while they neglect possible
distribution shifts between the query image and the support set. In contrast,
an experienced clinician can perceive and address such shifts by borrowing
information from the query image, then fine-tune or calibrate his (her) prior
cognitive model accordingly. …

arxiv cv image medical query segmentation