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首页> 外文期刊>Malaria Journal >Automated estimation of parasitaemia of Plasmodium yoelii-infected mice by digital image analysis of Giemsa-stained thin blood smears
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Automated estimation of parasitaemia of Plasmodium yoelii-infected mice by digital image analysis of Giemsa-stained thin blood smears

机译:通过吉姆萨染色的薄血涂片的数字图像分析自动估计约氏疟原虫感染小鼠的寄生虫血症

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Background Parasitaemia, the percentage of infected erythrocytes, is used to measure progress of experimental Plasmodium infection in infected hosts. The most widely used technique for parasitaemia determination is manual microscopic enumeration of Giemsa-stained blood films. This process is onerous, time consuming and relies on the expertise of the experimenter giving rise to person-to-person variability. Here the development of image-analysis software, named Plasmodium AutoCount, which can automatically generate parasitaemia values from Plasmodium-infected blood smears, is reported. Methods Giemsa-stained blood smear images were captured with a camera attached to a microscope and analysed using a programme written in the Python programming language. The programme design involved foreground detection, cell and infection detection, and spurious hit filtering. A number of parameters were adjusted by a calibration process using a set of representative images. Another programme, Counting Aid, written in Visual Basic, was developed to aid manual counting when the quality of blood smear preparation is too poor for use with the automated programme. Results This programme has been validated for use in estimation of parasitemia in mouse infection by Plasmodium yoelii and used to monitor parasitaemia on a daily basis for an entire challenge infection. The parasitaemia values determined by Plasmodium AutoCount were shown to be highly correlated with the results obtained by manual counting, and the discrepancy between automated and manual counting results were comparable to those found among manual counts of different experimenters. Conclusions Plasmodium AutoCount has proven to be a useful tool for rapid and accurate determination of parasitaemia from infected mouse blood. For greater accuracy when smear quality is poor, Plasmodium AutoCount, can be used in conjunction with Counting Aid.
机译:背景技术寄生虫血症(感染的红细胞百分比)用于衡量感染宿主中实验性疟原虫感染的进程。确定寄生虫血症的最广泛使用的技术是吉姆萨染色的血膜的手动显微镜计数。该过程是费力的,耗时的并且依赖于实验者的专业知识,从而导致人与人之间的可变性。此处报道了名为Plasmodium AutoCount的图像分析软件的开发,该软件可以从感染疟原虫的血液涂片中自动产生寄生虫血症值。方法用附在显微镜上的相机捕获吉姆萨染色的血液涂片图像,并使用以Python编程语言编写的程序进行分析。该程序设计涉及前台检测,细胞和感染检测以及伪造的命中过滤。通过使用一组代表性图像的校准过程来调整许多参数。开发了另一个用Visual Basic编写的程序Counting Aid,当血液涂片准备的质量太差而无法与自动程序一起使用时,可以帮助进行手动计数。结果该程序已被验证可用于估算约氏疟原虫感染小鼠的寄生虫病,并且可用于每天监测整个挑战性感染的寄生虫病。疟原虫自动计数确定的寄生虫血症值与手动计数获得的结果高度相关,自动计数和手动计数结果之间的差异可与不同实验人员的手动计数结果相媲美。结论Plasmodium AutoCount已被证明是一种快速,准确地确定感染的小鼠血液中寄生虫血症的有用工具。为了在涂片质量较差时获得更高的准确性,可以将Plasmodium AutoCount与Counting Aid一起使用。

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