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English(EN) Visualizing definitional divergence in high-dimensional data by manifold alignment: Application to 3D right ventricular strain computations

新方法可视化医学数据分析中的定义分歧

研究人员开发了一种新方法,用于可视化不同医学描述符定义如何影响数据分析。该方法使用流形对齐来匹配这些不同定义的潜在表示,并以心肌变形为例。该技术可以生成参数图来说明定义分歧,并已在玩具实验中进行了初步演示,随后应用于右心室应变数据。 AI

排序理由 该集群包含一篇详细介绍新数据分析方法的学术论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CV 阅读 →

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  1. arXiv cs.CV TIER_1 English(EN) · Maxime Di Folco, Gabriel Bernardino, Patrick Clarysse, Nicolas Duchateau ·

    Visualizing definitional divergence in high-dimensional data by manifold alignment: Application to 3D right ventricular strain computations

    arXiv:2501.12178v2 Announce Type: replace Abstract: Medical imaging studies often rely on a single sample per subject, assuming it is representative of their physiological traits. However, variations in how input descriptors are defined or computed (e.g. due to a lack of consensu…