Stain Specific Standardization of Whole-Slide Histopathological Images
Stain Specific Standardization of Whole-Slide Histopathological Images
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DOI：
10.1109/tmi.2015.2476509
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发表时间：
2016-02-01
影响因子：
10.6
通讯作者：
van der Laak, Jeroen A. W. M.
中科院分区：
文献类型：
--
作者：
Bejnordi, Babak Ehteshami;Litjens, Geert;van der Laak, Jeroen A. W. M.
苏木精和伊红（H&E）染色的组织学载玻片的颜色和强度的变化可能会妨碍定量图像分析的有效性。本文提出了一种全自动算法标准化的全载玻片组织病理学图像，以减少这些变化的影响。所提出的算法，被称为全载玻片图像颜色分类器（WSICS），利用颜色和空间信息分类到不同的染色成分的图像像素。将色调-饱和度-密度颜色模型中每个染色成分的色度和密度分布对齐，以匹配模板全载玻片图像（WSI）的相应分布。在两个数据集上评估了WSICS算法的性能。第一个来源于125个H&E染色的淋巴结WSI，从3名患者中取样，并在一周的不同日子在5个不同的实验室中染色。第二组包括大鼠肝切片的30个H&E染色的WSI。使用第一个数据集的定性和定量评估的结果表明，WSICS算法优于竞争的方法，在实现颜色恒定性。WSICS算法始终产生归一化中值强度测量的最小标准偏差和变异系数。使用第二个数据集，我们评估了我们的算法对已经发表的坏死量化系统的性能的影响。该系统的性能显着提高，利用WSICS算法。经验评估的结果共同证明了所提出的标准化算法的潜在贡献，以提高诊断的准确性和一致性，在计算机辅助诊断的组织病理学数据。
Variations in the color and intensity of hematoxylin and eosin (H&E) stained histological slides can potentially hamper the effectiveness of quantitative image analysis. This paper presents a fully automated algorithm for standardization of whole-slide histopathological images to reduce the effect of these variations. The proposed algorithm, called whole-slide image color standardizer (WSICS), utilizes color and spatial information to classify the image pixels into different stain components. The chromatic and density distributions for each of the stain components in the hue-saturation-density color model are aligned to match the corresponding distributions from a template whole-slide image (WSI). The performance of the WSICS algorithm was evaluated on two datasets. The first originated from 125 H&E stained WSIs of lymph nodes, sampled from 3 patients, and stained in 5 different laboratories on different days of the week. The second comprised 30 H&E stained WSIs of rat liver sections. The result of qualitative and quantitative evaluations using the first dataset demonstrate that the WSICS algorithm outperforms competing methods in terms of achieving color constancy. The WSICS algorithm consistently yields the smallest standard deviation and coefficient of variation of the normalized median intensity measure. Using the second dataset, we evaluated the impact of our algorithm on the performance of an already published necrosis quantification system. The performance of this system was significantly improved by utilizing the WSICS algorithm. The results of the empirical evaluations collectively demonstrate the potential contribution of the proposed standardization algorithm to improved diagnostic accuracy and consistency in computer-aided diagnosis for histopathology data.