使用具有深度学习功能的便携式成像流式细胞仪无标记检测贾第鞭毛虫包囊
Label-free detection of Giardia lamblia cysts using a deep learning-enabled portable imaging flow cytometer
摘要：
我们报告了一种现场便携且经济高效的成像流式细胞仪，该细胞仪使用深度学习来准确检测水样中的蓝氏贾第鞭毛虫囊肿，体积通量为100 mL/h。该流式细胞仪使用无透镜彩色全息成像来捕获和重建连续流动样品中微观物体的相位和强度图像，并在不使用任何标签或荧光团的情况下实时自动识别贾第虫囊。成像流式细胞仪置于尺寸为19 cm x 19 cm x 16 cm的环境密封外壳中，重1.6 kg。我们证明，这种便携式成像流式细胞仪耦合到笔记本电脑可以检测和定量，在实时，低水平的贾第虫污染（例如，<10个包囊/50 mL）。该方法的现场便携式和无标签的性质有可能允许在资源有限的环境中快速和自动筛选饮用水供应，以检测水生寄生虫和监测用于水处理的过滤器的完整性。
英文摘要：
We report a field-portable and cost-effective imaging flow cytometer that uses deep learning to accurately detect Giardia lamblia cysts in water samples at a volumetric throughput of 100 mL/h. This flow cytometer uses lensfree color holographic imaging to capture and reconstruct phase and intensity images of microscopic objects in a continuously flowing sample, and automatically identifies Giardia Lamblia cysts in real-time without the use of any labels or fluorophores. The imaging flow cytometer is housed in an environmentally-sealed enclosure with dimensions of 19 cm x 19 cm x 16 cm and weighs 1.6 kg. We demonstrate that this portable imaging flow cytometer coupled to a laptop computer can detect and quantify, in real-time, low levels of Giardia contamination (e.g., <10 cysts per 50 mL) in both freshwater and seawater samples. The field-portable and label-free nature of this method has the potential to allow rapid and automated screening of drinking water supplies in resource limited settings in order to detect waterborne parasites and monitor the integrity of the filters used for water treatment.
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