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浆液性积液中淋巴细胞的纹理分析。一种数学形态学方法。

Textural analysis of lymphoid cells in serous effusions. A mathematical morphologic approach.

作者信息

Moragas A, García-Bonafé M, de Torres I, Sans M

机构信息

Department of Pathology, Ciutat Sanitaria Universitaria Vall d'Hebron, Barcelona, Spain.

出版信息

Anal Quant Cytol Histol. 1993 Jun;15(3):165-70.

PMID:8347256
Abstract

Nuclear texture of reactive and well-differentiated neoplastic lymphocytes from serous effusions was studied by an approach based on principles of mathematical morphology. Density features were obtained before and after gray level nuclear image transformation by morphologic closing (dilation followed by erosion) and application of a top-hat function, which detects light or dense spots with a determined width and contrast. Five cases of benign reactive lymphocytic serous effusions and 11 cases of effusions in well-differentiated lymphocytic lymphomas were analyzed retrospectively. Each lymphoid cell was characterized by 24 densitometric features. Rank-order transformation was used for linear discriminant analysis given non-normal distributions of variables. In a first model formed by pooling all cells, discriminant function distinguished between 110 reactive and 216 malignant lymphocytes in the learning set and between 111 reactive and 226 malignant lymphocytes in the test set with better than 81% accuracy in both. In a second model, correct classification of cases as reactive or malignant was achieved in 5/5 reactive and 11/11 malignant lymphoid effusions. The results indicate that mathematical morphologic transformations of the gray level image may be an effective adjunct to other textural descriptors of cellular atypia, especially in the differential diagnosis of lymphoid serous effusions.

摘要

采用基于数学形态学原理的方法,对浆液性积液中反应性和高分化肿瘤性淋巴细胞的核纹理进行了研究。通过形态学闭运算(先膨胀后腐蚀)和应用顶帽函数(用于检测具有确定宽度和对比度的亮斑或暗斑)对灰度核图像进行变换前后,获取密度特征。回顾性分析了5例良性反应性淋巴细胞性浆液性积液和11例高分化淋巴细胞性淋巴瘤的积液。每个淋巴细胞由24个密度特征表征。由于变量分布不呈正态分布,采用秩次变换进行线性判别分析。在由所有细胞合并形成的第一个模型中,判别函数在学习集中区分了110个反应性淋巴细胞和216个恶性淋巴细胞,在测试集中区分了111个反应性淋巴细胞和226个恶性淋巴细胞,两者的准确率均优于81%。在第二个模型中,5例反应性和11例恶性淋巴样积液的病例均被正确分类为反应性或恶性。结果表明,灰度图像的数学形态学变换可能是细胞异型性其他纹理描述符的有效辅助手段,尤其是在淋巴样浆液性积液的鉴别诊断中。

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