Smeulders A W, Leyte-Veldstra L, Ploem J S, Cornelisse C J
J Histochem Cytochem. 1979 Jan;27(1):199-203. doi: 10.1177/27.1.374575.
Texture parameters of the nuclear chromatin pattern can contribute to the automated classification of specimens on the basis of single cell analysis in cervical cytology. Current texture parameters are abstract and therefore hamper understanding. In this paper texture parameters are described that can be derived from the chromatin pattern after segmentation of the nuclear image. These texture parameters are more directly related to the visual properties of the chromatin pattern. The image segmentation procedure is based on a region grow algorithm which specifically isolates high chromatin density. The texture analysis method has been tested on a data set of images of 112 cervical nuclei on photographic negatives digitized with a step size of 0.125 micron. The preliminary results of a classification trial indicate that these visually interpretable parameters have promising discriminatory power for the distinction between negative and positive specimens.
在宫颈细胞学的单细胞分析基础上，核染色质模式的纹理参数有助于标本的自动分类。当前的纹理参数较为抽象，因此妨碍了理解。本文描述了一些纹理参数，这些参数可从核图像分割后的染色质模式中得出。这些纹理参数与染色质模式的视觉特性更直接相关。图像分割程序基于一种区域生长算法，该算法专门分离高染色质密度区域。纹理分析方法已在一组112个宫颈细胞核图像数据集上进行了测试，这些图像来自以0.125微米步长数字化的照相底片。分类试验的初步结果表明，这些具有视觉可解释性的参数在区分阴性和阳性标本方面具有可观的判别能力。
