TAMISeg uses text prompts and semantic distillation from a frozen DINOv3 teacher inside a consistency-aware encoder and scale-adaptive decoder to outperform prior uni- and multi-modal methods on polyp and COVID-19 segmentation datasets.
Swin-Unet: Unet-like pure transformer for medical image segmentation,
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TAMISeg: Text-Aligned Multi-scale Medical Image Segmentation with Semantic Encoder Distillation
TAMISeg uses text prompts and semantic distillation from a frozen DINOv3 teacher inside a consistency-aware encoder and scale-adaptive decoder to outperform prior uni- and multi-modal methods on polyp and COVID-19 segmentation datasets.