scholarly journals Structured illumination microscopy with noise-controlled image reconstructions

2021 ◽  
Author(s):  
Carlas S. Smith ◽  
Johan A. Slotman ◽  
Lothar Schermelleh ◽  
Nadya Chakrova ◽  
Sangeetha Hari ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Resolving Power ◽  
Noise Model ◽  
Physical Parameters ◽  
Structured Illumination ◽  
Reconstruction Algorithms ◽  
Structured Illumination Microscopy ◽  
Signal To Noise ◽  
Trade Off ◽  
Noise Ratio

AbstractSuper-resolution structured illumination microscopy (SIM) has become a widely used method for biological imaging. Standard reconstruction algorithms, however, are prone to generate noise-specific artefacts that limit their applicability for lower signal-to-noise data. Here, we present a physically realistic noise model that explains the structured noise artefact and that is used to motivate new complementary reconstruction approaches. True Wiener-filtered SIM optimizes contrast given the available signal-to-noise ratio, flat-noise SIM fully overcomes the structured noise artefact while maintaining resolving power. Both methods eliminate ad-hoc user adjustable reconstruction parameters in favour of physical parameters, enhancing objectivity. The new reconstructions point to a trade-off between contrast and a natural noise appearance. This trade-off can be partly overcome by additional notch filtering, but at the expense of a decrease in signal-to-noise ratio. The benefits of the proposed approaches are demonstrated on focal adhesion and tubulin samples in 2D and 3D, and on nano-fabricated fluorescent test patterns.

Analytical model for the signal-to-noise-ratio of drift tube ion mobility spectrometers

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ansgar T. Kirk ◽  
Alexander Bohnhorst ◽  
Stefan Zimmermann
Keyword(s):  
Ion Mobility ◽  
Drift Tube ◽  
Signal To Noise Ratio ◽  
Resolving Power ◽  
Operating Point ◽  
Optimum Operating ◽  
Signal To Noise ◽  
Experimental Parameters ◽  
Noise Ratio ◽  
Optimum Operating Point

Abstract While the resolving power of drift tube ion mobility spectrometers has been studied and modelled in detail over the past decades, no comparable model exists for the signal-to-noise-ratio. In this work, we develop an analytical model for the signal-to-noise-ratio of a drift tube ion mobility spectrometer based on the same experimental parameters used for modelling the resolving power. The resulting holistic model agrees well with experimental results and allows simultaneously optimizing both resolving power and signal-to-noise-ratio. Especially, it reveals several unexpected relationships between experimental parameters. First, even though reduced initial ion packet widths result in fewer injected ions and reduced amplifier widths result in more noise, the resulting shift of the optimum operating point when reducing both simultaneously leads to a constant signal-to-noise-ratio. Second, there is no dependence of the signal-to-noise-ratio at the optimum operating point on the drift length, as again the resulting shift of the optimum operating point causes all effects to compensate each other.

scholarly journals Signal-to-Noise Ratio and Astronomical Fourier Transform Spectroscopy

1988 ◽  
Vol 132 ◽  
pp. 71-78
Author(s):  
J. P. Maillard
Keyword(s):  
Fourier Transform ◽  
Signal To Noise Ratio ◽  
Resolving Power ◽  
High Resolution Spectroscopy ◽  
Signal To Noise ◽  
Array Detectors ◽  
Noise Ratio ◽  
The Fourier Transform ◽  
Large Telescopes ◽  
Very High

The multiplex properties of the Fourier Transform Spectrometer (FTS) can be considered as disadvantageous with modern detectors and large telescopes, the dominant noise source being no longer in most applications the detector noise. Nevertheless, a FTS offers a gain in information and other instrumental features remain: flexibility in choosing resolving power up to very high values, large throughput, essential in high–resolution spectroscopy with large telescopes, metrologic accuracy, automatic substraction of parasitic background. The signal–to–noise ratio in spectra can also be improved: by limiting the bandwidth with cold filters or even cold dispersers, by matching the instrument to low background foreoptics and high–image quality telescopes. The association with array detectors provides the solution for the FTS to regain its full multiplex advantage.

scholarly journals Design optimisation of permanently installed monitoring system for polycrystalline materials

2020 ◽  
pp. 147592172095019
Author(s):  
Yuan Liu ◽  
Peter B. Nagy ◽  
Peter Cawley
Keyword(s):  
Surface Area ◽  
Monitoring System ◽  
Signal To Noise Ratio ◽  
Coarse Grained ◽  
Polycrystalline Materials ◽  
Depth Range ◽  
Bulk Wave ◽  
Signal To Noise ◽  
Trade Off ◽  
Noise Ratio

This article presents a design procedure for structural health monitoring systems based on bulk wave ultrasonic sensors for structures fabricated from polycrystalline materials. When designing a monitoring system, maximum coverage per transducer is a general requirement in order for the system to be economic. For coarse-grained polycrystalline materials, monitoring is often made challenging by low signal-to-noise ratios caused by grain scattering. Therefore, when designing a monitoring system for these materials, in addition to the economic requirement, it needs to be ensured that an adequate signal-to-noise ratio can be obtained throughout the monitoring volume. This typically introduces a trade-off between volume coverage per transducer and sensitivity that must be investigated. In this article, this trade-off is studied and a methodology using signal-to-noise maps is presented to design the system, that is, choose the optimal transducer parameters and placement. First, a combined analytical and numerical approach is used to generate a signal-to-noise map. Then, the influence of various factors on signal-to-noise ratio is investigated. Finally, two representative examples, with different criteria, are given to illustrate the methodology. In one example, the full surface area of the testpiece is covered with transducers and the optimum gives the deepest coverage. The other one aims to achieve the minimum fractional surface area that has to be covered with transducers to monitor a narrow depth range far from the surface, which has a potential application in weld monitoring. Results show that the optimum is likely to be at much lower frequency than typically used in inspection, as tracking signals with time gives sensitivity gains. Experiments were carried out to illustrate that higher volume coverage can be obtained at lower frequencies.

Super-resolution methods in MRI: Can they improve the trade-off between resolution, signal-to-noise ratio, and acquisition time?

2012 ◽  
Vol 68 (6) ◽  
pp. 1983-1993 ◽  
Author(s):  
Esben Plenge ◽  
Dirk H. J. Poot ◽  
Monique Bernsen ◽  
Gyula Kotek ◽  
Gavin Houston ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Super Resolution ◽  
Acquisition Time ◽  
Signal To Noise ◽  
Trade Off ◽  
Noise Ratio

Error Analysis for Estimation of Trace Vapor Concentration Pathlength in Stack Plumes

2003 ◽  
Vol 57 (6) ◽  
pp. 614-621 ◽  
Author(s):  
Neal B. Gallagher ◽  
Barry M. Wise ◽  
David M. Sheen
Keyword(s):  
Remote Sensing ◽  
Error Analysis ◽  
Near Infrared ◽  
Signal To Noise Ratio ◽  
Chemical Vapor ◽  
Noise Model ◽  
Vapor Concentration ◽  
Signal To Noise ◽  
Sensing Applications ◽  
Noise Ratio

Near-infrared hyperspectral imaging is finding utility in remote sensing applications such as detection and quantification of chemical vapor effluents in stack plumes. Optimizing the sensing system or quantification algorithms is difficult because reference images are rarely well characterized. The present work uses a radiance model for a down-looking scene and a detailed noise model for dispersive and Fourier transform spectrometers to generate well-characterized synthetic data. These data were used with a classical least-squares-based estimator in an error analysis to obtain estimates of different sources of concentration-pathlength quantification error in the remote sensing problem. Contributions to the overall quantification error were the sum of individual error terms related to estimating the background, atmospheric corrections, plume temperature, and instrument signal-to-noise ratio. It was found that the quantification error depended strongly on errors in the background estimate and second-most on instrument signal-to-noise ratio. Decreases in net analyte signal (e.g., due to low analyte absorbance or increasing the number of analytes in the plume) led to increases in the quantification error as expected. These observations have implications on instrument design and strategies for quantification. The outlined approach could be used to estimate detection limits or perform variable selection for given sensing problems.

Resolution performance of Wiener filters

Geophysics ◽  
1983 ◽  
Vol 48 (7) ◽  
pp. 887-899 ◽  
Author(s):  
S. H. Bickel ◽  
D. R. Martinez
Keyword(s):  
Time Constant ◽  
Matched Filter ◽  
Signal To Noise Ratio ◽  
Wiener Filter ◽  
Resolving Power ◽  
General Definition ◽  
Resolution Time ◽  
Signal To Noise ◽  
Temporal Separation ◽  
Noise Ratio

To improve the resolution of seismic events, one often designs a Wiener inverse filter that optimally (in the least‐squares sense) transforms a measured source signature into a spike. When this filter is applied to seismic data, the bandwidth of any noise which is present increases along with the bandwidth of the signal. Thus the signal‐to‐noise ratio is degraded. To reduce signal ambiguity it is common practice to prewhiten the Wiener filter. Prewhitening the filter improves the output signal‐to‐ambient noise ratio, but at the same time it reduces resolution. The ability to resolve the temporal separation between events is determined by the resolution time constant which we define as the ratio of signal energy to peak signal power from the filter. For unfiltered wavelets the resolution time constant becomes the reciprocal of resolving power recently described by Widess (1982). For matched filter signals the resolution time constant can be regarded as the inverse of the frequency span of the signal. Although it is satisfying that the resolution time constant definition agrees with other measures of resolution, this more general definition has two major advantages. First, it incorporates the effect of filtering; second, it is easily generalized to incorporate the effects of noise by assuming that the filter is a Wiener filter. For a given amount of noise the Wiener filter is a generalization of the matched filter. Marine seismic wavelets demonstrate how reducing the noise level improves the resolution of a Wiener filter relative to a matched filter. For these wavelets a point of diminishing return is reached, such that, to realize a further small increase in resolution, a large increase in input signal‐to‐noise ratio is required to maintain interpretable information at the output.

scholarly journals Comparison of conventional and Si-photomultiplier-based PET systems for image quality and diagnostic performance

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Jenny Oddstig ◽  
Sigrid Leide Svegborn ◽  
Helen Almquist ◽  
Ulrika Bitzén ◽  
Sabine Garpered ◽  
...  
Keyword(s):  
Image Quality ◽  
Diagnostic Performance ◽  
Signal To Noise Ratio ◽  
Tnm Classification ◽  
Activity Level ◽  
Reconstruction Algorithms ◽  
Signal To Noise ◽  
Standardized Uptake Values ◽  
Pet Ct ◽  
Noise Ratio

Abstract Background A new generation of positron emission tomography with computed tomography (PET-CT) was recently introduced using silicon (Si) photomultiplier (PM)-based technology. Our aim was to compare the image quality and diagnostic performance of a SiPM-based PET-CT (Discovery MI; GE Healthcare, Milwaukee, WI, USA) with a time-of-flight PET-CT scanner with a conventional PM detector (Gemini TF; Philips Healthcare, Cleveland, OH, USA), including reconstruction algorithms per vendor’s recommendations. Methods Imaging of the National Electrical Manufacturers Association IEC body phantom and 16 patients was carried out using 1.5 min/bed for the Discovery MI PET-CT and 2 min/bed for the Gemini TF PET-CT. Images were analysed for recovery coefficients for the phantom, signal-to-noise ratio in the liver, standardized uptake values (SUV) in lesions, number of lesions and metabolic TNM classifications in patients. Results In phantom, the correct (> 90%) activity level was measured for spheres ≥17 mm for Discovery MI, whereas the Gemini TF reached a correct measured activity level for the 37-mm sphere. In patient studies, metabolic TNM classification was worse using images obtained from the Discovery MI compared those obtained from the Gemini TF in 4 of 15 patients. A trend toward more malignant, inflammatory and unclear lesions was found using images acquired with the Discovery MI compared with the Gemini TF, but this was not statistically significant. Lesion-to-blood-pool SUV ratios were significantly higher in images from the Discovery MI compared with the Gemini TF for lesions smaller than 1 cm (p < 0.001), but this was not the case for larger lesions (p = 0.053). The signal-to-noise ratio in the liver was similar between platforms (p = 0.52). Also, shorter acquisition times were possible using the Discovery MI, with preserved signal-to-noise ratio in the liver. Conclusions Image quality was better with Discovery MI compared to conventional Gemini TF. Although no gold standard was available, the results indicate that the new PET-CT generation will provide potentially better diagnostic performance.

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