LEUKOCYTE PATTERN-RECOGNITION
LEUKOCYTE PATTERN-RECOGNITION
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DOI：
10.1109/tsmc.1972.4309161
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发表时间：
1972-01-01
期刊：
影响因子：
--
通讯作者：
GOSE, EE
中科院分区：
文献类型：
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作者：
BACUS, JW;GOSE, EE
外周血白细胞自动分类的结果分为八个类别。分类是通过数字图像处理来实现的。这些类别是：小淋巴细胞、中淋巴细胞、大淋巴细胞、带状嗜中性粒细胞、分叶嗜中性粒细胞、嗜酸性粒细胞、嗜碱性粒细胞和单核细胞。使用八维多变量高斯分类器。从50 × 50点的数字图像中提取特征。这些特征是对核大小、核形状、核和细胞质纹理、细胞质颜色和细胞质着色纹理等视觉概念的测量。该数据集由1041个血细胞图像组成，并被分为523个细胞的训练集和518个细胞的独立测试集。这些细胞直接从用Wright染色剂染色的血液涂片中数字化。研究人员使用了20种不同的血液涂片，并在三年内从20人中收集了这些涂片。数据集的“真实”分类来自4名经验丰富的血液学技术人员。将它们的性能与自动分类器在细胞的绝对分类和估计群体的百分比组成（或血细胞分类计数）方面进行比较。所用的性能衡量标准是每个类的错误百分比。对于人类观察者和自动分类器，八个类别的绝对分类的平均百分比误差分别为8%和29%。
The results of an automated classification of the peripheral blood leukocytes into eight categories are presented. The classification was achieved by means of digital image processing. The categories were: small lymphocytes, medium lymphocytes, large lymphocytes, band neutrophils, segmented neutrophils, eosinophils, basophils, and monocytes. An eight-dimensional multivariate Gaussian classifier was used. The features were extracted from a 50 × 50 point digital image. These features were measures of such visual concepts as nuclear size, nuclear shape, nuclear and cytoplasmic texture, cytoplasm color, and cytoplasm colored texture. The data set consisted of 1041 blood cell images and were divided into a training set of 523 cells and an independent testing set of 518 cells. These cells were digitized directly from the blood smear, which was stained with Wright's stain. Twenty different blood smears were used and were collected over a three-year period from 20 people. The "true" classification of the data set was obtained from four experienced hematology technicians. Their performance was compared to the automated classifier both in terms of an absolute classification of cells and in terms of estimating the percentage composition of the population (or the blood cell differential count). The measure of performance used was the percentage error for each class. The mean percentage error for the eight classes in terms of an absolute classification was 8 and 29 percent for the human observers and the automated classiffier, respectively.