The Fourier-Adaptive Nonlinear Low-Rank Adaptor (FAN-LoRA), a novel frequency-decoupled fine-tuning architecture, is proposed, which achieves consistent improvements in average Dice scores and notable reductions in boundary errors, while maintaining a compact module size without compromising computational efficiency.
This work systematically investigates the role of text in multimodal medical image segmentation and proposes an Evidence Decoupling Decoder (EDD) based on evidential deep learning and deep supervision, finding that text affects predictions mainly through global semantic modulation rather than independent spatial locali...
InstEditSeg is proposed, a unified generative framework that reformulates medical segmentation as an instruction-driven image editing problem, and achieves accuracy competitive with strong discriminative baselines, and demonstrates concrete advantages of the generative formulation.
Zihao Liu, Zhe Zhu, Xuzi Shi· 0 citations
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