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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >A software package to improve image quality and isolation of objects of interest for quantitative stereology studies of rat hepatocarcinogenesis.
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A software package to improve image quality and isolation of objects of interest for quantitative stereology studies of rat hepatocarcinogenesis.

机译：一个用于提高图像质量和分离感兴趣对象的软件包，用于大鼠肝癌发生定量定量研究。

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In the studies of quantitative stereology of rat hepatocarcinogenesis, we have used image analysis technology (automatic particle analysis) to obtain data such as liver tissue area, size and location of altered hepatic focal lesions (AHF), and nuclei counts. These data are then used for three-dimensional estimation of AHF occurrence and nuclear labeling index analysis. These are important parameters for quantitative studies of carcinogenesis, for screening and classifying carcinogens, and for risk estimation. To take such measurements, structures or cells of interest should be separated from the other components based on the difference of color and density. Common background problems seen on the captured sample image such as uneven light illumination or color shading can cause severe problems in the measurement. Two application programs (BK_Correction and Pixel_Separator) have been developed to solve these problems. With BK_Correction, common background problems such as incorrect color temperature setting, color shading, and uneven light illumination background, can be corrected. With Pixel_Separator different types of objects can be separated from each other in relation to their color, such as seen with different colors in immunohistochemically stained slides. The resultant images of such objects separated from other components are then ready for particle analysis. Objects that have the same darkness but different colors can be accurately differentiated in a grayscale image analysis system after application of these programs.
机译：在大鼠肝癌发生的定量立体学研究中，我们使用了图像分析技术（自动颗粒分析）来获取数据，例如肝脏组织面积，肝局灶性病变（AHF）的大小和位置以及细胞核计数。然后将这些数据用于AHF发生的三维估计和核标记指数分析。这些是致癌作用定量研究，致癌物的筛选和分类以及风险评估的重要参数。要进行此类测量，应根据颜色和密度的差异将目标结构或细胞与其他组件分开。在捕获的样本图像上看到的常见背景问题，例如不均匀的光照或颜色阴影，可能会导致测量中的严重问题。开发了两个应用程序（BK_Correction和Pixel_Separator）来解决这些问题。使用BK_Correction，可以纠正常见的背景问题，例如不正确的色温设置，颜色阴影和不均匀的光照背景。使用Pixel_Separator，可以根据其颜色将不同类型的对象彼此分离，例如在免疫组织化学染色的载玻片中可以看到不同的颜色。然后可以将这些与其他组件分离的物体生成的图像准备好进行粒子分析。应用这些程序后，可以在灰度图像分析系统中准确区分具有相同暗度但颜色不同的对象。

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