Department of Biological Engineering, University of Missouri, Columbia, Missouri, USA.
Toxicol Mech Methods. 2003;13(3):213-20. doi: 10.1080/15376510309837.
Image-processing techniques were developed to assist histological analysis of rat spleen specimens stained for iron with Perl's Prussian blue. The stained areas in the splenic tissue images were segmented on the basis of color attributes. A series of image features was extracted to describe the subjective concept of blueness, an important attribute in the histological evaluation of blue-stained tissues. Feature extraction was based on statistical analysis. A neural network model was developed to predict pathologists' scores from selected image features. The model predicted pathologists' scores with an R 2 value of 0.86.
图像处理技术被开发出来，以协助用 Perl 的普鲁士蓝对铁染色的大鼠脾脏标本进行组织学分析。根据颜色属性对脾脏组织图像中的染色区域进行分割。提取了一系列图像特征来描述蓝色的主观概念，这是组织学评估蓝色染色组织的一个重要属性。特征提取基于统计分析。开发了一个神经网络模型，从选定的图像特征预测病理学家的评分。该模型预测病理学家的评分的 R 2 值为 0.86。
