New high-speed centre of mass method incorporating background subtraction for accurate determination of fluorescence lifetime
New high-speed centre of mass method incorporating background subtraction for accurate determination of fluorescence lifetime
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DOI：
10.1364/oe.24.006899
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发表时间：
2016-04-04
期刊：
影响因子：
3.8
通讯作者：
Henderson, Robert K.
中科院分区：
文献类型：
--
作者：
Poland, Simon P.;Erdogan, Ahmet T.;Henderson, Robert K.
我们演示了一种质心法（CMM）的实现，该方法结合背景减法，用于多焦点荧光寿命成像显微镜，以准确地确定使用Megaframe相机在活细胞成像中的荧光寿命。背景减法的加入解决了质心法的一个主要问题，即算法对背景信号的敏感性。该算法主要在硬件上实现，提供实时生命周期输出，并允许用户有效地压缩大量光子数据。而不是需要传输数千个光子到达时间，寿命是简单地表示为一个值，允许系统收集数据到脉冲堆积的限制，没有任何限制的数据传输速率。为了评估这种新的CMM算法与现有技术（即快速寿命测定和Levenburg-Marquardt）的性能，我们对瞬时转染FRET标准的活MCF-7人乳腺癌细胞进行了成像。我们表明，它在寿命精度和对兆帧相机像素之间的暗计数率（DCR）变化不敏感方面提供了显著的优势。与其他算法不同，不需要预期寿命的先验知识来执行寿命确定。这种技术提供实时寿命读数的能力使其对许多应用程序非常有用。(C) 2016年美国光学学会
We demonstrate an implementation of a centre-of-mass method (CMM) incorporating background subtraction for use in multifocal fluorescence lifetime imaging microscopy to accurately determine fluorescence lifetime in live cell imaging using the Megaframe camera. The inclusion of background subtraction solves one of the major issues associated with centre-of-mass approaches, namely the sensitivity of the algorithm to background signal. The algorithm, which is predominantly implemented in hardware, provides real-time lifetime output and allows the user to effectively condense large amounts of photon data. Instead of requiring the transfer of thousands of photon arrival times, the lifetime is simply represented by one value which allows the system to collect data up to limit of pulse pile-up without any limitations on data transfer rates. In order to evaluate the performance of this new CMM algorithm with existing techniques (i.e. rapid lifetime determination and Levenburg-Marquardt), we imaged live MCF-7 human breast carcinoma cells transiently transfected with FRET standards. We show that, it offers significant advantages in terms of lifetime accuracy and insensitivity to variability in dark count rate (DCR) between Megaframe camera pixels. Unlike other algorithms no prior knowledge of the expected lifetime is required to perform lifetime determination. The ability of this technique to provide real-time lifetime readout makes it extremely useful for a number of applications. (C) 2016 Optical Society of America