English(EN) GazeRefine: Expert Gaze as a Test-Time Prompt for Training-Free Medical Image Segmentation

GazeRefine 使用专家注视进行无训练的医学图像分割

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-02 04:00

研究人员开发了 GazeRefine，一个利用专家注视作为无训练医学图像分割提示的新颖框架。该方法将稀疏的注视点转换为前景和背景先验，然后在冻结的 DINOv3 特征空间中进行细化。GazeRefine 消除了对分割掩码、微调或梯度更新的需求，在息肉分割方面表现出色，在前列腺 MRI 分割方面取得了有竞争力的结果。 AI

影响这种无训练的方法可以显著减少医学成像任务中对广泛专家注释的需求。

排序理由该条目描述了一篇关于用于医学图像分割的新颖框架的最新研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Mohammed Oussama Benyahia, Marouane Tliba, Mohamed Amine Kerkouri, Taifour Yousra, Bin Wang, Max Bengtsson, Gorkem Durak, Elif Keles, Zuheng Ming, Marek Penhaker, Azeddine Beghdadi, Ulas Bagci, Aladine Chetouani · 2026-09-02 04:00

GazeRefine：专家视线作为无训练的测试时提示用于医学图像分割

arXiv:2609.01310v1 Announce Type: cross Abstract: Medical image segmentation remains difficult to scale because high-performing methods typically rely on dense expert annotations and task-specific training. We introduce GazeRefine, a training-free framework that uses gaze as an i…

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报道来源 [1]

GazeRefine：专家视线作为无训练的测试时提示用于医学图像分割

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