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Computational Pathology Analysis of TissueMicroarrays Predicts Survival of Renal Clear Cell Carcinoma Patients

机译:Tissuexicroarrays的计算病理学分析预测肾透明细胞癌患者的存活

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Renal cell carcinoma (RCC) can be diagnosed by histological tissue analysis where exact counts of cancerous cell nuclei are required. We propose a completely automated image analysis pipeline to predict the survival of RCC patients based on the analysis of immunohistochem-ical staining of MIB-1 on tissue microarrays. A random forest classifier detects cell nuclei of cancerous cells and predicts their staining. The classifier training is achieved by expert annotations of 2300 nuclei gathered from tissues of 9 different RCC patients. The application to a test set of 133 patients clearly demonstrates that our computational pathology analysis matches the prognostic performance of expert pathologists.
机译:通过组织学组织分析可以诊断肾细胞癌(RCC),其中需要癌细胞核的精确计数。我们提出了一种完全自动化的图像分析管道,以预测RCC患者的存活,基于分析MIB-1对组织微阵列的免疫组织染色。随机森林分类器检测癌细胞的细胞核并预测其染色。通过来自9例不同RCC患者的组织聚集的2300个核的专家注释实现了分类器培训。对133名患者的测试集的应用清楚地表明,我们的计算病理分析与专家病理学家的预后表现相匹配。

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