Statistical colour models: an automated digital image analysis method for quantification of histological biomarkers.
Statistical colour models: an automated digital image analysis method for quantification of histological biomarkers.
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DOI：
10.1186/s12938-016-0161-6
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发表时间：
2016-04-27
影响因子：
3.9
通讯作者：
Ilyas M
中科院分区：
文献类型：
--
作者：
Shu J;Dolman GE;Duan J;Qiu G;Ilyas M
颜色是定量免疫组织化学（IHC）图像分析中最重要的特征；免疫组化用于提供有关病因和确认恶性肿瘤的信息。统计建模是一种广泛应用于计算机视觉色彩检测的技术。我们已经开发了一个统计模型的颜色检测适用于检测染色染色的数字IHC图像。首先采用半自动采集的大量彩色像素对模型进行训练。为了加快训练和检测过程，我们去除了YCbCr色彩空间的亮度通道、Y通道，选择了128个最优直方图bins。使用最大似然分类器将数字幻灯片中的像素自动分类为阳性或阴性染色像素。ImageJ开发了基于模型的工具，用于量化利用免疫组化和组织化学鉴定的靶标。评估的目的是将计算机模型与人类评估进行比较。准备并获得了几个大型数据集，这些数据集来自不同颜色染色的人类食管癌、结肠癌和肝硬化。实验结果表明，基于模型的工具在棕色检测中比颜色反褶积和CMYK模型获得了更准确的结果，在粉红色检测中与颜色反褶积相当。我们还证明了所提出的模型在数据集之间几乎没有变化。本文介绍了一种稳健有效的统计模型。ImageJ中基于模型的交互工具可以创建统计模型的可视化表示并自动检测指定的颜色，它易于使用，并且可以在http://rsb.info.nih.gov/ij/plugins/ihc-toolbox/index.html上免费获得。不同用户对该工具的测试结果显示，观察者之间的差异很小。
Colour is the most important feature used in quantitative immunohistochemistry (IHC) image analysis; IHC is used to provide information relating to aetiology and to confirm malignancy. Statistical modelling is a technique widely used for colour detection in computer vision. We have developed a statistical model of colour detection applicable to detection of stain colour in digital IHC images. Model was first trained by massive colour pixels collected semi-automatically. To speed up the training and detection processes, we removed luminance channel, Y channel of YCbCr colour space and chose 128 histogram bins which is the optimal number. A maximum likelihood classifier is used to classify pixels in digital slides into positively or negatively stained pixels automatically. The model-based tool was developed within ImageJ to quantify targets identified using IHC and histochemistry. The purpose of evaluation was to compare the computer model with human evaluation. Several large datasets were prepared and obtained from human oesophageal cancer, colon cancer and liver cirrhosis with different colour stains. Experimental results have demonstrated the model-based tool achieves more accurate results than colour deconvolution and CMYK model in the detection of brown colour, and is comparable to colour deconvolution in the detection of pink colour. We have also demostrated the proposed model has little inter-dataset variations. A robust and effective statistical model is introduced in this paper. The model-based interactive tool in ImageJ, which can create a visual representation of the statistical model and detect a specified colour automatically, is easy to use and available freely at http://rsb.info.nih.gov/ij/plugins/ihc-toolbox/index.html. Testing to the tool by different users showed only minor inter-observer variations in results.