Brugal G, Quirion C, Vassilakos P
Anal Quant Cytol Histol. 1986 Sep;8(3):187-94.
The cell image analysis of urinary sediments was performed using a SAMBA 200 system. Cell profiles were created using 18 parameters related to size, shape, densitometry and chromatin texture. Learning sets of about 50 cell images per class were constructed for bening, degenerated benign, atypical, malignant and degenerated malignant urothelial cell types as well as for squamous epithelial and white blood cell types. A four-level hierarchic decision tree involving a discriminant analysis at each node was designed and then evaluated against a test set of 700 cells from the various classes. All of the cell images involved in this study were acquired from Papanicolaou-stained specimens obtained for routine screening. In spite of some misclassification errors, the analysis of the occurrence of cells in the various classes, especially the percentage of cells classified as suspicious (both atypical and malignant cells), by the SAMBA 200 system resulted in the separate clustering of the positive specimens (49 carcinomas grade II and higher) and the negative ones (26 benign samples). The preliminary results suggest that the cell population features (occurrence rate of cells in the various classes and mean cell profile within a class) may be of diagnostic value in designing a classifier dedicated to the prescreening of urinary sediments for the detection of bladder cancers.
使用SAMBA 200系统对尿沉渣进行细胞图像分析。利用与大小、形状、密度测定和染色质纹理相关的18个参数创建细胞轮廓。针对良性、退变良性、非典型、恶性和退变恶性尿路上皮细胞类型以及鳞状上皮和白细胞类型，构建了每组约50个细胞图像的学习集。设计了一个四级层次决策树，在每个节点进行判别分析，然后针对来自不同类别的700个细胞的测试集进行评估。本研究中涉及的所有细胞图像均从用于常规筛查的巴氏染色标本中获取。尽管存在一些误分类错误，但SAMBA 200系统对各类细胞出现情况的分析，特别是将细胞分类为可疑（非典型和恶性细胞）的百分比，导致阳性标本（49例II级及以上癌）和阴性标本（26例良性样本）分别聚类。初步结果表明，细胞群体特征（各类细胞的出现率和一类内的平均细胞轮廓）在设计用于尿沉渣预筛查以检测膀胱癌的分类器时可能具有诊断价值。
