How to measure diagnosis-associated information in virtual slides.
How to measure diagnosis-associated information in virtual slides.
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DOI：
10.1186/1746-1596-6-s1-s9
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发表时间：
2011-03-30
影响因子：
2.6
通讯作者：
Kayser G
中科院分区：
文献类型：
--
作者：
Kayser K;Görtler J;Borkenfeld S;Kayser G
诊断相关信息在组织切片中的分布通常是空间依赖性的。一个可靠的选择载玻片区域包含最重要的信息，以获得相关的诊断是虚拟显微镜的主要任务。可以使用三种不同的算法来选择适当的视场：1）与图论相结合的对象相关分割; 2）与时间序列相关联的纹理分析;以及3）基于几何图元的几何统计。这些方法可以通过滑动技术（即，具有固定帧的视场选择），以及通过聚类分析。这些方法的实施需要在晕影校正和灰度值分布方面对图像进行标准化以及确定适当的放大率（仅方法1）。颜色空间的主成分分析可以显著减少所需的计算时间。方法3是基于灰度值依赖的分割，然后使用（相关联的）最小生成树和Voronoi的邻域条件的构造的图论应用。这三种方法已被应用于包括不同器官（结肠，肺，胸膜，胃，甲状腺）和不同放大倍数的大型组织学图像集，试验结果在所有三种方法的视野的可重复性和正确的选择。不同的算法可以组合成视场选择的基本技术，并且可以导出“图像信息”的一般理论。将讨论所应用的方法的优点和限制。
The distribution of diagnosis-associated information in histological slides is often spatial dependent. A reliable selection of the slide areas containing the most significant information to deriving the associated diagnosis is a major task in virtual microscopy. Three different algorithms can be used to select the appropriate fields of view: 1) Object dependent segmentation combined with graph theory; 2) time series associated texture analysis; and 3) geometrical statistics based upon geometrical primitives. These methods can be applied by sliding technique (i.e., field of view selection with fixed frames), and by cluster analysis. The implementation of these methods requires a standardization of images in terms of vignette correction and gray value distribution as well as determination of appropriate magnification (method 1 only). A principle component analysis of the color space can significantly reduce the necessary computation time. Method 3 is based upon gray value dependent segmentation followed by graph theory application using the construction of (associated) minimum spanning tree and Voronoi’s neighbourhood condition. The three methods have been applied on large sets of histological images comprising different organs (colon, lung, pleura, stomach, thyroid) and different magnifications, The trials resulted in a reproducible and correct selection of fields of view in all three methods. The different algorithms can be combined to a basic technique of field of view selection, and a general theory of “image information” can be derived. The advantages and constraints of the applied methods will be discussed.