English(EN) ProtoPur: Prototype-Purity Pseudo-Labeling for Weakly Supervised Instance Learning in Pathology

ProtoPur方法通过弱监督增强病理图像分析

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-15 04:00

研究人员推出了一种新颖的计算病理学弱监督实例学习方法ProtoPur。该技术利用原型纯度伪标签，即使在只有有限的袋级标签的情况下，也能从基础模型特征中提取特定类别的证据。ProtoPur旨在提高全切片图像分析中的实例级性能，而无需密集的、手动标注。 AI

影响 ProtoPur有望通过利用弱标签，实现更高效、更准确的病理图像分析，从而可能改进诊断工具。

排序理由该集群包含一篇详细介绍计算病理学中弱监督新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Chen Shu, Chengyang Zhang, Boyu Fu, Ting Yin, Wenchuan Zhang, Jie Chen, Yuhao Yi, Hong Bu · 2026-10-15 04:00

ProtoPur：病理学弱监督实例学习的原型纯度伪标签

arXiv:2610.15669v2 Announce Type: replace-cross Abstract: Weak bag-level labels are widely available in computational pathology, whereas reliable instance-level annotations for whole-slide images remain expensive and ambiguous. Weakly supervised multiple instance learning (MIL) a…