AI RESEARCH
Few-Shot Distribution-Aligned Flow Matching for Data Synthesis in Medical Image Segmentation
arXiv CS.CV
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ArXi:2604.02868v1 Announce Type: cross Data heterogeneity hinders clinical deployment of medical image analysis models, and generative data augmentation helps mitigate this issue. However, recent diffusion-based methods that synthesize image-mask pairs often ignore distribution shifts between generated and real images across scenarios, and such mismatches can markedly degrade downstream performance.