2020
DOI: 10.1093/bioinformatics/btaa635
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RainbowSTORM: an open-source ImageJ plug-in for spectroscopic single-molecule localization microscopy (sSMLM) data analysis and image reconstruction

Abstract: Summary Spectroscopic single-molecule localization microscopy (sSMLM) simultaneously captures the spatial locations and full spectra of stochastically emitting fluorescent single-molecules. It provides an optical platform to develop new multi-molecular and functional imaging capabilities. While several open-source software suites provide sub-diffraction localization of fluorescent molecules, software suites for spectroscopic analysis of sSMLM data remain unavailable. RainbowSTORM is an open-s… Show more

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Cited by 9 publications
(5 citation statements)
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References 16 publications
(25 reference statements)
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“…Remote-sensing image processing technology is utilised in the realm of resources and environmental science to monitor natural catastrophes such as floods, forest fires, and earthquakes, analyse pollution levels, and explore mineral, groundwater, and marine resources [12]. In industry, computer vision allows robots to do components' inspection and automated assembly, as well as other repetitive operations, with great accuracy [13]. Militarily, image processing technology plays an important role in target location, tracking, and weapon guidance.…”
Section: Introductionmentioning
confidence: 99%
“…Remote-sensing image processing technology is utilised in the realm of resources and environmental science to monitor natural catastrophes such as floods, forest fires, and earthquakes, analyse pollution levels, and explore mineral, groundwater, and marine resources [12]. In industry, computer vision allows robots to do components' inspection and automated assembly, as well as other repetitive operations, with great accuracy [13]. Militarily, image processing technology plays an important role in target location, tracking, and weapon guidance.…”
Section: Introductionmentioning
confidence: 99%
“…For each sample, 32,000 frames were taken with an exposure time of 40 ms to ensure good coverage of binding events in the polymers. Processing of the image stacks by standard single-molecule localization algorithms with Fiji plugins, Thunderstorm, and RainbowStorm, , we obtain a matrix of event data with spatial coordinates, emission photons, spectral wavelength, etc., to allow us to reconstruct the super-resolved images by summing all events (Figure S2). Then, to perform quantitative analysis at a single-fiber level, postprocessing of the data was performed using a previously reported workflow .…”
Section: Resultsmentioning
confidence: 99%
“…The localization les which contain the single-molecule coordinates (X, Y, T) and the raw single-molecule uorescence spectrum of AF647 and CF680 were obtained via Thunder-STORM and RainbowSTORM for Fiji. 25,26 Additionally, the rst 1500 frames were ltered out to wait for the proper STORM blinking to occur. Furthermore, a density lter (radius 80 nm, neighbors 80) was applied to lter out the nonspecic localizations which occur like sparse points in the eld of view.…”
Section: Sr-dstorm Quanticationmentioning
confidence: 99%