Abstract：
For many parasitic diseases, the microscopic examination of clinical samples such as urine and stool still serves as the diagnostic reference standard, primarily because microscopes are accessible and cost-effective. However, conventional microscopy is laborious, requires highly skilled personnel, and is highly subjective. Requirements for skilled operators, coupled with the cost and maintenance needs of the microscopes, which is hardly done in endemic countries, presents grossly limited access to the diagnosis of parasitic diseases in resource-limited settings. The urgent requirement for the management of tropical diseases such as schistosomiasis, which is now focused on elimination, has underscored the critical need for the creation of access to easy-to-use diagnosis for case detection, community mapping, and surveillance. In this paper, we present a low-cost automated digital microscope-the Schistoscope-which is capable of automatic focusing and scanning regions of interest in prepared microscope slides, and automatic detection of Schistosoma haematobium eggs in captured images. The device was developed using widely accessible distributed manufacturing methods and off-the-shelf components to enable local manufacturability and ease of maintenance. For proof of principle, we created a Schistosoma haematobium egg dataset of over 5000 images captured from spiked and clinical urine samples from field settings and demonstrated the automatic detection of Schistosoma haematobium eggs using a trained deep neural network model. The experiments and results presented in this paper collectively illustrate the robustness, stability, and optical performance of the device, making it suitable for use in the monitoring and evaluation of schistosomiasis control programs in endemic settings.
摘要：
对于许多寄生虫病，尿液和粪便等临床样本的显微镜检查仍可作为诊断参考标准，主要是因为显微镜是可访问的和具有成本效益的。然而,传统的显微镜是费力的，需要高技能的人才，而且是高度主观的。对熟练操作人员的要求,再加上显微镜的成本和维护需求，这在流行国家很难做到，在资源有限的环境中，寄生虫疾病诊断的机会非常有限。对血吸虫病等热带病管理的迫切要求,现在专注于消除，强调了创建易于使用的诊断以进行病例检测的关键需求，社区制图,和监视。在本文中,我们提出了一种低成本的自动化数字显微镜-血吸镜-它能够自动聚焦和扫描感兴趣的区域在准备的显微镜载玻片，并在捕获的图像中自动检测血吸虫卵。该设备是使用可广泛使用的分布式制造方法和现成的组件开发的，以实现本地可制造性和易于维护。为了证明原理，我们创建了一个血吸虫血吸虫卵数据集,该数据集包含从野外设置的加标尿液和临床尿液样本中捕获的超过5000张图像,并演示了使用经过训练的深度神经网络模型自动检测血吸虫血吸虫血吸虫卵.本文的实验和结果共同说明了鲁棒性，稳定性,和器件的光学性能，使其适用于流行环境中血吸虫病控制计划的监测和评估。
