High Dynamic Range Fluorescence Imaging

Vinegoni, Claudio; Feruglio, Paolo Fumene; Weissleder, Ralph

doi:10.1109/jstqe.2018.2881608

Cited by 20 publications

(13 citation statements)

References 34 publications

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“…High background often arises from sub-optimal experimental design, and although it is subtracted from fluorescent intensity measurements, it is best to initially image the regions of interest with as little background signal as possible 28 . A high dynamic range, with a minimum ~10-fold difference, is required to successfully determine if signal is considered background or signal of interest 29 . False positive spots refer to signal residing outside of the cell boundaries, often due to poorly cleaned coverslips, insufficient washing following hybridization, or probe aggregation that occurs when probes self-associate 30 .…”

Section: Discussionmentioning

confidence: 99%

Single Cell Analysis Of Transcriptionally Active Alleles By Single Molecule FISH

Mistry

Singh

Mancini

et al. 2020

JoVE

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Gene transcription is an essential process in cell biology, and allows cells interpret and respond to internal and external cues. Traditional bulk population methods (Northern blot, PCR, and RNAseq) that measure mRNA levels lack the ability to provide information on cell-to-cell variation in responses. Precise single cell and allelic visualization and quantification is possible via single molecule RNA fluorescence in situ hybridization (smFISH). RNA-FISH is performed by hybridizing target RNAs with labeled oligonucleotide probes. These can be imaged in medium/ high throughput modalities, and, through image analysis pipelines, provide quantitative data on both mature and nascent RNAs, all at the single cell level. The fixation, permeabilization, hybridization and imaging steps have been optimized in our lab over many years using the model system described herein, which results in successful and robust single cell analysis of smFISH labeling. The main goal with sample preparation and processing is to produce high quality images characterized by a high signal-to-noise ratio to reduce false positives and provide data that are more accurate. Here we offer our protocol describing the pipeline from sample preparation to data analysis in conjunction with suggestions and optimization steps to tailor to specific samples.

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Section: Discussionmentioning

confidence: 99%

Single Cell Analysis Of Transcriptionally Active Alleles By Single Molecule FISH

Mistry

Singh

Mancini

et al. 2020

JoVE

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“…If this is the case, the acquired images will then present different regions with fluorescence intensities saturated or below the background. The result is that we obtain a loss of the image informative content effectively reducing the detectors' bit depths, 31 with the impossibility to differentiate among different structures and giving rise to severely impaired image quality.…”

Section: Methodsmentioning

confidence: 99%

Extended dynamic range imaging for noise mitigation in fluorescence anisotropy imaging

2020

Self Cite

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Significance: Fluorescence polarization (FP) and fluorescence anisotropy (FA) microscopy are powerful imaging techniques that allow to translate the common FP assay capabilities into the in vitro and in vivo cellular domain. As a result, they have found potential for mapping drugprotein or protein-protein interactions. Unfortunately, these imaging modalities are ratiometric in nature and as such they suffer from excessive noise even under regular imaging conditions, preventing accurate image-feature analysis of fluorescent molecules behaviors. Aim: We present a high dynamic range (HDR)-based FA imaging modality for improving image quality in FA microscopy. Approach: The method exploits ad hoc acquisition schemes to extend the dynamic range of individual FP channels, allowing to obtain FA images with increased signal-to-noise ratio. Results: A direct comparison between FA images obtained with our method and the standard, clearly indicates how an HDR-based FA imaging approach allows to obtain high-quality images, with the ability to correctly resolve image features at different values of FA and over a substantially higher range of fluorescence intensities. Conclusion: The method presented is shown to outperform standard FA imaging microscopy narrowing the spread of the propagated error and yielding higher quality images. The method can be effectively and routinely used on any commercial imaging system and could be also translated to other microscopy ratiometric imaging modalities.

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“…In such an approach, a feedback mechanism is utilized which monitors the emerging signal strength and accordingly provides suitable feedback to a tunable excitation source to regulate the excitation power (Ji et al, 2008;Yang et al, 2017;Chu et al 2007Chu et al , 2010Hoebe et al, 2007). Another approach is to employ a real-time high dynamic range (HDR) imaging (Vinegoni et al, 2016(Vinegoni et al, , 2019Feruglio et al, 2020), which collects multiple low dynamic range (LDR) images over multiple optically-separated detection channels, and subsequently fuse them together to form the HDR image. However, implementing these techniques requires dedicated hardware configurations.…”

Section: Introductionmentioning

confidence: 99%

A rapid denoised contrast enhancement method digitally mimicking an adaptive illumination in submicron-resolution neuronal imaging

Borah

Sun

2022

iScience

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Optical neuronal imaging often shows ultrafine structures, such as a nerve fiber, coexisting with ultrabright structures, such as a soma with a substantially higher fluorescence-protein concentration. Owing to experimental and environmental factors, a laser-scanning multiphoton optical microscope (MPM) often encounters a high-frequency background noise that might contaminate such weak-intensity ultrafine neuronal structures. A straightforward contrast enhancement often leads to the saturation of the brighter ones, and might further amplify the high-frequency background noise. We report a digital approach called rapid denoised contrast enhancement (DCE), which digitally mimics a hardware-based adaptive/controlled illumination technique by means of digitally optimizing the signal strengths and hence the visibility of such weak-intensity structures while mostly preventing the saturation of the brightest ones. With large field-of-view (FOV) two-photon excitation fluorescence (TPEF) neuronal imaging, we validate the effectiveness of DCE over state-ofthe-art digital image processing algorithms. With compute-unified-device-architecture (CUDA)-acceleration, a real-time DCE is further enabled with a reduced time complexity.

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High Dynamic Range Fluorescence Imaging

Cited by 20 publications

References 34 publications

Single Cell Analysis Of Transcriptionally Active Alleles By Single Molecule FISH

Single Cell Analysis Of Transcriptionally Active Alleles By Single Molecule FISH

Extended dynamic range imaging for noise mitigation in fluorescence anisotropy imaging

A rapid denoised contrast enhancement method digitally mimicking an adaptive illumination in submicron-resolution neuronal imaging

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