Rózycka M, Lenczowski S, Sawicki W, Barańska W, Ostrowski K
Cytometry. 1982 Jan;2(4):244-8. doi: 10.1002/cyto.990020408.
Optical diffraction was tested on electron micrographs of normal and malformed myelin sheaths as a method for semiautomatic quantitative analysis of tissue specimens. Both normal and malformed myelin sheaths were chosen for the analysis because of their characteristic internal structure and its alteration as a result of malformation. Optical diffraction patterns were obtained by means of an optical diffractometer coupled with a digital detector. The spacing and arrangement of the components of various types of myelin sheath were automatically calculated and determined and the results were verified with discriminant analysis. Out of 27 parameters of the radial and out of 25 parameters of the angular distributions of diffracted light intensity, 6 and 11, respectively, were found to have good discriminative power and were used for classification of myelin sheaths. The accuracy of automatic classification was tested by comparison with myelin sheath types of known origin. The samples visually similar by their appearance, e.g. control and regenerating myelin sheaths, were automatically classified with accuracy of 69%, whereas others were classified appropriately with 88-100% accuracy. It is believed that this kind of analysis may successfully be applied for specimens of other tissues and/or organs.
作为一种对组织标本进行半自动定量分析的方法,对正常和畸形髓鞘的电子显微照片进行了光学衍射测试。选择正常和畸形髓鞘进行分析,是因为它们具有独特的内部结构以及因畸形而产生的结构改变。通过与数字探测器相连的光学衍射仪获得光学衍射图样。自动计算并确定了各类髓鞘成分的间距和排列情况,并用判别分析对结果进行了验证。在衍射光强度的径向分布的27个参数和角向分布的25个参数中,分别有6个和11个参数具有良好的判别能力,并用于髓鞘的分类。通过与已知来源的髓鞘类型进行比较,测试了自动分类的准确性。外观视觉上相似的样本,如对照和再生髓鞘,自动分类的准确率为69%,而其他样本的分类准确率为88% - 100%。据信,这种分析方法可成功应用于其他组织和/或器官的标本。