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使用低成本互补金属氧化物半导体(CMOS)网络摄像头的图像堆叠方法来提高荧光检测的灵敏度。

Image stacking approach to increase sensitivity of fluorescence detection using a low cost complementary metal-oxide-semiconductor (CMOS) webcam.

作者信息

Balsam Joshua, Bruck Hugh Alan, Kostov Yordan, Rasooly Avraham

机构信息

Division of Biology, Office of Science and Engineering, FDA, Silver Spring, MD 20993, United States ; University of Maryland College Park (UMCP), College Park, MD 20742, United States.

出版信息

Sens Actuators B Chem. 2012;171-172:141-147. doi: 10.1016/j.snb.2012.02.003.

Abstract

Optical technologies are important for biological analysis. Current biomedical optical analyses rely on high-cost, high-sensitivity optical detectors such as photomultipliers, avalanched photodiodes or cooled CCD cameras. In contrast, Webcams, mobile phones and other popular consumer electronics use lower-sensitivity, lower-cost optical components such as photodiodes or CMOS sensors. In order for consumer electronics devices, such as webcams, to be useful for biomedical analysis, they must have increased sensitivity. We combined two strategies to increase the sensitivity of CMOS-based fluorescence detector. We captured hundreds of low sensitivity images using a Webcam in video mode, instead of a single image typically used in cooled CCD devices.We then used a computational approach consisting of an image stacking algorithm to remove the noise by combining all of the images into a single image. While video mode is widely used for dynamic scene imaging (e.g. movies or time-lapse photography), it is not used to capture a single static image, which removes noise and increases sensitivity by more than thirty fold. The portable, battery-operated Webcam-based fluorometer system developed here consists of five modules: (1) a low cost CMOS Webcam to monitor light emission, (2) a plate to perform assays, (3) filters and multi-wavelength LED illuminator for fluorophore excitation, (4) a portable computer to acquire and analyze images, and (5) image stacking software for image enhancement. The samples consisted of various concentrations of fluorescein, ranging from 30 μM to 1000 μM, in a 36-well miniature plate. In the single frame mode, the fluorometer's limit-of-detection (LOD) for fluorescein is ∼1000 μM, which is relatively insensitive. However, when used in video mode combined with image stacking enhancement, the LOD is dramatically reduced to 30 μM, sensitivity which is similar to that of state-of-the-art ELISA plate photomultiplier-based readers. Numerous medical diagnostics assays rely on optical and fluorescence readers. Our novel combination of detection technologies, which is new to biodetection may enable the development of new low cost optical detectors based on an inexpensive Webcam (<$10). It has the potential to form the basis for high sensitivity, low cost medical diagnostics in resource-poor settings.

摘要

光学技术对生物分析很重要。当前的生物医学光学分析依赖于高成本、高灵敏度的光学探测器,如光电倍增管、雪崩光电二极管或冷却电荷耦合器件相机。相比之下,网络摄像头、手机和其他流行的消费电子产品使用的是低灵敏度、低成本的光学元件,如光电二极管或互补金属氧化物半导体传感器。为了使诸如网络摄像头之类的消费电子设备能够用于生物医学分析,它们必须提高灵敏度。我们结合了两种策略来提高基于互补金属氧化物半导体的荧光探测器的灵敏度。我们使用网络摄像头以视频模式捕获数百张低灵敏度图像,而不是像冷却电荷耦合器件设备通常那样捕获单张图像。然后,我们使用一种由图像叠加算法组成的计算方法,通过将所有图像组合成一张图像来去除噪声。虽然视频模式广泛用于动态场景成像(如电影或延时摄影),但它不用于捕获单张静态图像,而单张静态图像可以去除噪声并将灵敏度提高三十多倍。这里开发的基于网络摄像头的便携式、电池供电荧光计系统由五个模块组成:(1)用于监测光发射的低成本互补金属氧化物半导体网络摄像头,(2)用于进行检测的平板,(3)用于荧光团激发的滤光片和多波长发光二极管照明器,(4)用于采集和分析图像的便携式计算机,以及(5)用于图像增强的图像叠加软件。样品是在一个36孔微型平板中含有浓度范围从30微摩尔到1000微摩尔的各种浓度的荧光素。在单帧模式下,荧光计对荧光素的检测限约为1000微摩尔,相对不灵敏。然而,当在视频模式下结合图像叠加增强使用时,检测限大幅降低至30微摩尔,其灵敏度与基于酶联免疫吸附测定平板光电倍增管的最先进读数器相似。许多医学诊断检测依赖于光学和荧光读数器。我们这种新型的检测技术组合,在生物检测领域是全新的,可能会推动基于廉价网络摄像头(不到10美元)开发新型低成本光学探测器。它有可能为资源匮乏地区的高灵敏度、低成本医学诊断奠定基础。

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