Landini Gabriel, Randell David A, Breckon Toby P, Han Ji Wan
Oral Pathology Unit, School of Dentistry, College of Medical and Dental Sciences, University of Birmingham, St. Chad's Queensway, Birmingham B4 6NN, UK.
Anal Quant Cytol Histol. 2010 Feb;32(1):30-8.
To explore tissue organization based on the geometry of cell neighborhoods in histologic preparations.
Local complexity of solid tissues was measured in images of discrete tissue compartments. Exclusive areas associated with cell nuclei (v-cells) were computed using a watershed transform of the nuclear staining intensity. Mathematical morphology was used to define neighborhood membership, distances and identify complete nested neighborhoods. Neighborhood complexity was estimated as the scaling of the number of neighbors relative to reference v-cells.
The methodology applied to hematoxylin-eosin-stained sections from normal, dysplastic and neoplastic oral epithelium revealed that the scaling exponent, over a finite range of neighborhood levels, is nonunique and fractional. While scaling values overlapped across classes, the average was marginally higher in neoplastic than in dysplastic and normal epithelia. The best classificatory power of the exponent was 58% correct classification into 3 diagnostic classes (11 levels) and 83% between dysplastic and neoplastic classes (13 levels).
V-cell architecture retains features of the original tissue classes and demonstrates an increase in tissue disorder in neoplasia. This methodology seems suitable for extracting information from tissues where identification of cell boundaries (and therefore segmentation into individual cells) is unfeasible.
基于组织学切片中细胞邻域的几何结构探索组织构成。
在离散组织区域的图像中测量实体组织的局部复杂性。使用细胞核染色强度的分水岭变换计算与细胞核相关的专属区域（v细胞）。运用数学形态学定义邻域成员、距离并识别完整的嵌套邻域。邻域复杂性通过相对于参考v细胞的邻居数量缩放来估计。
应用于正常、发育异常和肿瘤性口腔上皮苏木精-伊红染色切片的方法显示，在有限的邻域水平范围内，缩放指数是非唯一且分数的。虽然缩放值在不同类别间有重叠，但肿瘤性上皮的平均值略高于发育异常和正常上皮。该指数的最佳分类能力为将其正确分类到3个诊断类别（11个水平）中的正确率为58%，在发育异常和肿瘤性类别之间（13个水平）的正确率为83%。
v细胞结构保留了原始组织类别的特征，并显示出肿瘤形成过程中组织无序性增加。该方法似乎适用于从难以识别细胞边界（因此无法分割成单个细胞）的组织中提取信息。
