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VQ-Seg: Vector-Quantized Token Perturbation for Semi-Supervised Medical Image Segmentation

📝 Summary:
VQ-Seg introduces vector quantization to replace dropout with a controllable perturbation module for semi-supervised medical image segmentation. It uses a dual-branch architecture and foundation model guidance to maintain performance. VQ-Seg outperforms state-of-the-art methods on various medical...

🔹 Publication Date: Published on Jan 15

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2601.10124
• PDF: https://arxiv.org/pdf/2601.10124
• Project Page: https://github.com/script-Yang/VQ-Seg
• Github: https://github.com/script-Yang/VQ-Seg

Datasets citing this paper:
https://huggingface.co/datasets/yscript/ACDC-PNG

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https://xn--r1a.website/DataScienceT

#MedicalImageSegmentation #SemiSupervisedLearning #VectorQuantization #DeepLearning #ComputerVision