论文标题
通过污渍反卷积在He染色的滑梯上实现胶原蛋白定量并休息的He-Hes
Enabling Collagen Quantification on HE-stained Slides Through Stain Deconvolution and Restained HE-HES
论文作者
论文摘要
在组织学中，细胞外基质中胶原蛋白的存在既具有诊断性和预后值，又可以通过将藏红花（S）添加到常规的苏木精和曙红（HE）染色中来突出显示。但是，除了基于法国的实验室外，通常不添加藏红花，因为病理学家习惯了他的病理学家。在本文中，我们表明可以单独量化He图像的胶原蛋白含量并以数字方式创建HES图像。为此，我们训练了一个UNET来预测HE图像的藏红花密度。我们创建了一个注册，休息的HE-HES幻灯片的数据集，并使用HES图像上的污渍反卷积提取了藏红花浓度作为地面真相。我们的模型在3倍测试集上达到了0.0668 $ \ pm $ 0.0002（藏红花值）的平均绝对误差。我们希望我们的方法可以帮助改善临床工作流程，同时降低实验室的试剂成本。
In histology, the presence of collagen in the extra-cellular matrix has both diagnostic and prognostic value for cancer malignancy, and can be highlighted by adding Saffron (S) to a routine Hematoxylin and Eosin (HE) staining. However, Saffron is not usually added because of the additional cost and because pathologists are accustomed to HE, with the exception of France-based laboratories. In this paper, we show that it is possible to quantify the collagen content from the HE image alone and to digitally create an HES image. To do so, we trained a UNet to predict the Saffron densities from HE images. We created a dataset of registered, restained HE-HES slides and we extracted the Saffron concentrations as ground truth using stain deconvolution on the HES images. Our model reached a Mean Absolute Error of 0.0668 $\pm$ 0.0002 (Saffron values between 0 and 1) on a 3-fold testing set. We hope our approach can aid in improving the clinical workflow while reducing reagent costs for laboratories.
