Preston K, Dekker A
Anal Quant Cytol. 1980 Sep;2(3):203-30.
The initial development of algorithms for the analysis of multicolor multicellular images of liver tissue sections is described. Using a three-color image recorded by an automated light microscope, a sequence of cellular logic operators was applied to the task of differentiating between hepatocyte and leukocyte nuclei in a section taking advantage of both spatial and chromatic features, namely, that hepatocyte nuclei usually appear larger than those of leukocytes and, in red illumination, are likely to be more transparent. Optimally, the developed algorithms properly differentiated 90% of the hepatocyte nuclie and 85% of the leukocyte nuclie; this performance level appears to equal that of a microscopist. The microscopist, however, rarely analyses all cells; thus, computer differentiation of cells eventually may provide an important new dimension to clinical histopathology.
本文描述了用于分析肝组织切片多色多细胞图像的算法的初步开发。利用自动光学显微镜记录的三色图像，应用一系列细胞逻辑运算符，借助空间和色彩特征，对切片中的肝细胞核和白细胞核进行区分，即肝细胞核通常比白细胞核大，且在红色照明下可能更透明。理想情况下，所开发的算法能正确区分90%的肝细胞核和85%的白细胞核；这种性能水平似乎与显微镜专家相当。然而，显微镜专家很少分析所有细胞；因此，细胞的计算机分化最终可能为临床组织病理学提供一个重要的新维度。
