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Automatic quantification of IHC stain in breast TMA using colour analysis

机译:使用颜色分析自动定量IHC染色的IHC染色

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Abstract Immunohistochemical (IHC) biomarkers in breast tissue microarray (TMA) samples are used daily in pathology departments. In recent years, automatic methods to evaluate positive staining have been investigated since they may save time and reduce errors in the diagnosis. These errors are mostly due to subjective evaluation. The aim of this work is to develop a density tool able to automatically quantify the positive brown IHC stain in breast TMA for different biomarkers. To avoid the problem of colour variation and make a robust tool independent of the staining process, several colour standardization methods have been analysed. Four colour standardization methods have been compared against colour model segmentation. The standardization methods have been compared by means of NBS colour distance. The use of colour standardization helps to reduce noise due to stain and histological sample preparation. However, the most reliable and robust results have been obtained by combining the HSV and RGB colour models for segmentation with the HSB channels. The segmentation provides three outputs based on three saturation values for weak, medium and strong staining. Each output image can be combined according to the type of biomarker staining. The results with 12 biomarkers were evaluated and compared to the segmentation and density calculation done by expert pathologists. The Hausdorff distance, sensitivity and specificity have been used to quantitative validate the results. The tests carried out with 8000 TMA images provided an average of 95.94% accuracy applied to the total tissue cylinder area. Colour standardization was used only when the tissue core had blurring and fading stain and the expert could not evaluate them without a pre-processing.
机译:摘要免疫组织化学(IHC)乳腺组织微阵列(TMA)样品的生物标志物每天在病理部门使用。近年来,已经研究了评估阳性染色的自动方法,因为它们可以节省时间并减少诊断中的误差。这些错误主要是由于主观评估。这项工作的目的是开发一种能够在不同的生物标志物中自动量化乳腺TMA中的正棕色IHC染色的密度工具。为避免颜色变化的问题并使其独立于染色过程的鲁棒工具,已经分析了几种颜色标准化方法。已经将四种颜色标准化方法与颜色模型分割进行了比较。通过NBS颜色距离进行了标准化方法。颜色标准化的使用有助于降低由于染色和组织学样品制备引起的噪声。然而,通过将HSV和RGB颜色模型与HSB通道组合进行分割来获得最可靠和稳健的结果。该分割基于弱,中等和强染色的三个饱和值提供三个输出。每个输出图像可以根据生物标记染色的类型组合。评估12个生物标志物的结果,并与专家病理学家的分割和密度计算进行比较。 Hausdorff距离,敏感性和特异性已被用于定量验证结果。使用8000TMA图像进行的测试,平均提供95.94%的精度,施加到总组织缸面积。只有当组织核心模糊和衰落污染时,才使用颜色标准化,并且专家无法在没有预处理的情况下评估它们。

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