English(EN) End-to-End Cell Detection via Instance-aware Graph Modeling

新框架模拟细胞相互作用以改进检测

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-15 04:00

研究人员开发了一种新颖的端到端细胞检测和分类框架，该框架将视觉特征与关系建模相结合。该方法利用动态图构建模块，根据特征相似性和空间邻近性在细胞实例之间建立关系。然后，实例感知图网络通过过滤和重组特征来精炼这些实例，最终将它们聚合为融合外观和关系证据的拓扑状态。与现有方法相比，该方法在多个数据集上均表现出优越的性能。 AI

影响这种新的建模方法可以通过改进细胞检测和分类来提高病理学诊断的准确性。

排序理由该集群包含一篇在 arXiv 上发表的研究论文，详细介绍了一种新的细胞检测方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Ruochen Liu, Yalin Zheng, Jingxin Liu, Jianfeng Zhang, Shoujun Huang, Dexing Kong, Haofeng Li, Wei Lou · 2026-09-15 04:00

通过实例感知图模型实现端到端细胞检测

arXiv:2609.15354v1 Announce Type: cross Abstract: Accurate cell detection and classification are crucial for pathological analysis, directly affecting diagnostic accuracy and treatment planning. To capture complex cellular interactions beyond visual appearance within the tumor mi…

本文如何被排名

报道来源 [1]

通过实例感知图模型实现端到端细胞检测

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