首页> 外文期刊>Journal of clinical laboratory analysis. >An automated image analysis system can be beneficial in preclassification of leucocytes in children with hematological disease.
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An automated image analysis system can be beneficial in preclassification of leucocytes in children with hematological disease.

机译:自动化的图像分析系统在血液系统疾病患儿白细胞的预分类中可能是有益的。

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摘要

This study was aimed to evaluate the analytical performance of an automated image analysis system (a pilot model of Diff Master() Octavia) for the preclassification of leucocytes in children with hematological disease. Manual microscopy performed by pediatric hematologists was used as the reference method. Five mature cell class and blasts were evaluated. Diff Master Octavia correctly preclassified 87.4% of all leucocytes with a high reproducibility. The overall accuracy was found to be 93.0%. Clinical sensitivity was 97.7% and specificity was 76.0%. The average time per slide for Diff Master() Octavia was 2.3 min lower than that of manual method. Our results indicated that the Diff Master() Octavia can detect and preclassify leucocytes accurately; therefore, it can be used as an efficient and fast method in pediatric hematology routine.
机译:这项研究的目的是评估自动图像分析系统(Diff Master()Octavia的试验模型)对血液系统疾病患儿白细胞的预分类的分析性能。小儿血液科医师进行的手动显微镜检查被用作参考方法。评价了五个成熟细胞类别和原始细胞。 Diff Master Octavia对所有白细胞中的87.4%进行了正确的预分类,具有很高的重现性。发现总体准确度为93.0%。临床敏感性为97.7%,特异性为76.0%。 Diff Master()Octavia每张幻灯片的平均时间比手动方法少2.3分钟。我们的结果表明,Diff Master()Octavia可以准确地检测和预分类白细胞。因此,它可以作为儿科血液学常规检查中的一种有效而快速的方法。

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