Digital pathology has shown great importance for diagnostic purposes in the digital age by integrating basic image features into multi-modality information. We quantify the degree of correlation between the multiple texture features from H&E images and polarization parameter sets derived from Mueller matrix images of the same sample to provide more microstructural information for assisting diagnosis. The experimental result shows the correlations between texture feature and polarization parameter via Pearson coefficients. Polarization parameters t₁, D_L and the depolarization parameter Δ correlated with image texture features Tamura_Fcon and Tamura_Frgh, and can be used as powerful tools to quantitatively characterize cell nuclei related with tumor progression in breast pathological tissues. Polarization parameters δ and r_L associated with the image texture feature Tamura_Flin have great potential for the quantitative characterization of proliferative fibers produced by inflammation. Furthermore, polarization parameters have the advantages of stable recognition in low resolution images. This work validates the associations between image texture features and polarization parameters and the merit of polarization imaging methods in low-resolution situations.

中文翻译：

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组织病理学中图像纹理和极化特征的比较

通过将基本图像特征集成到多模态信息中，数字病理学在数字时代对诊断目的已显示出极大的重要性。我们量化了来自H＆E图像的多个纹理特征与源自同一样本的Mueller矩阵图像的偏振参数集之间的相关程度，以提供更多的微结构信息以帮助诊断。实验结果通过皮尔逊系数显示出纹理特征与偏振参数之间的相关性。极化参数吨₁，d_大号和去极化参数Δ与图像纹理结构相关设有Tamura_Fcon和Tamura_Frgh，并且可以用作定量表征与乳房病理组织中肿瘤进展相关的细胞核的有力工具。与图像纹理特征Tamura_Flin相关的偏振参数δ和r _L具有定量表征由炎症产生的增生纤维的巨大潜力。此外，偏振参数具有在低分辨率图像中稳定识别的优点。这项工作验证了图像纹理特征和偏振参数之间的关联以及在低分辨率情况下偏振成像方法的优点。