2019
DOI: 10.1021/acs.analchem.9b02804
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Postrecording Pixel-Reconstruction Approach for Correcting the Lateral Drifts in Surface Plasmon Resonance Microscope

Abstract: Surface plasmon resonance microscope (SPRM) sample stage inevitably suffers from lateral drifts as a result of many environmental factors including thermal fluctuation, mechanical vibration, and relaxation. It places great obstacles to time-lapsed imaging and measurements that need high spatial resolution or long recording time. Existing solutions often require experimental efforts such as the addition of optical markers together with piezoelectric stage-based active feedback configurations. Herein, we propose… Show more

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Cited by 10 publications
(7 citation statements)
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“…Plotting the location of the SNPs in a time sequence yields their trajectory during the sublimation process (Figure d). Note that the drift of the optical imaging system has been precorrected using a post-recording pixel reconstruction approach that we previously developed . Moreover, adjacent individuals in the same field of view exhibited rather different trajectories, thus excluding the influence of environmental disturbance such as drift of stage (Figure S6).…”
Section: Resultsmentioning
confidence: 99%
“…Plotting the location of the SNPs in a time sequence yields their trajectory during the sublimation process (Figure d). Note that the drift of the optical imaging system has been precorrected using a post-recording pixel reconstruction approach that we previously developed . Moreover, adjacent individuals in the same field of view exhibited rather different trajectories, thus excluding the influence of environmental disturbance such as drift of stage (Figure S6).…”
Section: Resultsmentioning
confidence: 99%
“…Two beams of perpendicular incident light with the same wavelength are used for SPR imaging, leading to two perpendicular SPR patterns of the same nanobubble in one image. A cross-correlation method is subsequently adopted to calculate the localization of nanobubble. , Unlike 2D Gaussian fitting, cross-correlation depends on the correlation coefficient (similarity) of the images, which is particularly suitable for irregular patterns . Representative correlation images of the conventional one-beam and dual-beam SPR patterns are displayed in Figure .…”
Section: Resultsmentioning
confidence: 99%
“…The collision process of AuNPs was monitored in real time with the trackMate plugin in ImageJ commercial software. Since low-frequency noise due to optical background has an influence on the reconstructed images, the background was removed by using a medium-value algorithm, 23 or subtracting the first frame.…”
Section: ■ Introductionmentioning
confidence: 99%