Rowley Mark I, Coolen Anthonius C C, Vojnovic Borivoj, Barber Paul R
Institute for Mathematical and Molecular Biomedicine, King's College London, London, United Kingdom.
Cancer Research UK and Medical Research Council Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford, United Kingdom.
PLoS One. 2016 Jun 29;11(6):e0158404. doi: 10.1371/journal.pone.0158404. eCollection 2016.
We present novel Bayesian methods for the analysis of exponential decay data that exploit the evidence carried by every detected decay event and enables robust extension to advanced processing. Our algorithms are presented in the context of fluorescence lifetime imaging microscopy (FLIM) and particular attention has been paid to model the time-domain system (based on time-correlated single photon counting) with unprecedented accuracy. We present estimates of decay parameters for mono- and bi-exponential systems, offering up to a factor of two improvement in accuracy compared to previous popular techniques. Results of the analysis of synthetic and experimental data are presented, and areas where the superior precision of our techniques can be exploited in Förster Resonance Energy Transfer (FRET) experiments are described. Furthermore, we demonstrate two advanced processing methods: decay model selection to choose between differing models such as mono- and bi-exponential, and the simultaneous estimation of instrument and decay parameters.
我们提出了用于分析指数衰减数据的新型贝叶斯方法，该方法利用每个检测到的衰减事件所携带的证据，并能够稳健地扩展到高级处理。我们的算法是在荧光寿命成像显微镜（FLIM）的背景下提出的，并且特别关注以前所未有的精度对时域系统（基于时间相关单光子计数）进行建模。我们给出了单指数和双指数系统衰减参数的估计值，与以前流行的技术相比，精度提高了两倍。文中展示了合成数据和实验数据的分析结果，并描述了我们的技术在Förster共振能量转移（FRET）实验中可利用其卓越精度的领域。此外，我们展示了两种高级处理方法：衰减模型选择，用于在不同模型（如单指数和双指数）之间进行选择，以及仪器参数和衰减参数的同时估计。
