AI RESEARCH
MAE-Based Self-Supervised Pretraining for Data-Efficient Medical Image Segmentation Using nnFormer
arXiv CS.CV
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ArXi:2604.22854v1 Announce Type: new Transformer architectures, including nnFormer,have nstrated promising results in volumetric medical image segmentation by being able to capture long-range spatial interactions. Although they have high performance, these models need large quantities of labeled