2018
DOI: 10.1117/1.oe.57.3.031305
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Fluorescence decay data analysis correcting for detector pulse pile-up at very high count rates

Abstract: Using Time-Correlated Single Photon Counting (TCSPC) for the purpose of fluorescence lifetime measurements is usually limited in speed due to pile-up. With modern instrumentation this limitation can be lifted significantly but some artefacts due to frequent merging of closely spaced detector pulses (detector pulse pile-up) remains an issue to be addressed. We propose here a data analysis method correcting for this type of artefact and the resulting systematic errors. It physically models the photon losses due … Show more

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Cited by 20 publications
(17 citation statements)
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“…Users may also synchronize the photon counter with their laser pulses through its reference clock input (1, see methods), enabling several applications such as fluorescence lifetime imaging (6,9,15), image restoration (7), temporal demultiplexing of interleaved beamlets (3,9) and post-hoc gated noise reduction. Moreover, as PySight provides direct access to the photon count in each voxel, it allows implementing photon mis-detections correction algorithms that can further increase the dynamic range of the ren-dered images (6,10,16,20). Finally, although PySight has been built around specific hardware, the open-source code can handle any list of photon arrival times through a welldocumented application interface (see Supplementary Figure S1c and Supplementary Note L. It is extensible to any imaging method based on single-pixel (bucket) detectors, including fast compressive bioimaging (13,19).…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Users may also synchronize the photon counter with their laser pulses through its reference clock input (1, see methods), enabling several applications such as fluorescence lifetime imaging (6,9,15), image restoration (7), temporal demultiplexing of interleaved beamlets (3,9) and post-hoc gated noise reduction. Moreover, as PySight provides direct access to the photon count in each voxel, it allows implementing photon mis-detections correction algorithms that can further increase the dynamic range of the ren-dered images (6,10,16,20). Finally, although PySight has been built around specific hardware, the open-source code can handle any list of photon arrival times through a welldocumented application interface (see Supplementary Figure S1c and Supplementary Note L. It is extensible to any imaging method based on single-pixel (bucket) detectors, including fast compressive bioimaging (13,19).…”
Section: Discussionmentioning
confidence: 99%
“…If the threshold level was selected properly, no counts should be acquired. 16. Turn on the PMT in light-tight conditions and start another multiscaler acquisition.…”
Section: Supplementarymentioning
confidence: 99%
“…For the highest level of performance, an emission filter can be optionally used. In addition, to prevent pile-up for the detector [27], as is typical for many TCSPC implementations, a neutral density (ND) filter can be inserted between the excitation source and the LCW to attenuate excitation power. In the proposed system, a FUJIFILM 10% thin-film ND filter is used.…”
Section: System Implementationmentioning
confidence: 99%
“…In this protocol, we measured at higher count rates as the system had a very short deadtime. So, in this case we choose rapid Reconvolution as it corrects for pulse pile up artefacts [8]. For FLIM acquired with conventional electronics and detectors then n-Exponential Reconvolution would be an appropriate model to use.…”
mentioning
confidence: 99%