论文标题
使用具有深度学习的便携式成像流式细胞仪的贾第鞭毛虫lamblia囊肿的无标签检测
Label-free detection of Giardia lamblia cysts using a deep learning-enabled portable imaging flow cytometer
论文作者
论文摘要
我们报告了一种可野外且具有成本效益的成像流式细胞仪，该流式细胞仪使用深度学习来准确检测水样中的贾第鞭毛虫囊肿，以100 mL/h的体积吞吐量。该流式细胞仪使用无透明的颜色全息成像来在连续流动的样品中捕获和重建显微镜的相位图像和强度图像，并自动在不使用任何标签或荧光酚的情况下自动识别贾第鞭毛虫lamblia囊肿。成像流式细胞仪位于环境密封的外壳中，尺寸为19 cm x 19 cm x 16 cm，重1.6千克。我们证明，与笔记本计算机耦合的该便携式成像流式细胞仪可以实时检测和量化淡水和海水样品中的低水平贾第鞭毛虫污染（例如，<10囊肿）。该方法的现场便携性和无标签性质有可能在资源有限的设置中快速自动筛选饮用水供应，以检测水传播的寄生虫并监视用于水处理的过滤器的完整性。
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.
