Axial resolution enhancement for light sheet fluorescence microscopy via using the subtraction method

Le, Vannhu; Wang, Xiaona; Kuang, Cuifang; Xu, Liang

doi:10.1117/1.oe.57.10.103107

Cited by 8 publications

(3 citation statements)

References 21 publications

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“…Other, more complex, illumination and detection schemes are suitable to improve axial resolution and optical sectioning at the same time. Examples include structured illumination [14], confocal slit detection [15], STED [16], RESOLFT [31], tiling [32,33], axially scanned light sheets [34] and computational reconstruction of images acquired with complementary light sheets [35,36]. However, the improved performance comes at a cost such as, for example, excess light exposure or reduction in achievable imaging speed.…”

Section: Discussionmentioning

confidence: 99%

How to define and optimize axial resolution in light-sheet microscopy: a simulation-based approach

Remacha¹,

Friedrich²,

Vermot³

et al. 2019

Biomed. Opt. Express

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How thick is your light sheet?" is a question that has been asked frequently after talks showing impressive renderings of 3D data acquired by a light-sheet microscope. This question is motivated by the fact that most of the time the thickness of the light-sheet is uniquely associated to the axial resolution of the microscope. However, the link between light-sheet thickness and axial resolution has never been systematically assessed and it is still unclear how both are connected. The question is not trivial because commonly employed measures cannot readily be applied or do not lead to easily interpretable results for the many different types of light sheet. Here, we introduce a set of intuitive measures that helps to define the relationship between light sheet thickness and axial resolution by using simulation data. Unexpectedly, our analysis revealed a trade-off between better axial resolution and thinner light-sheet thickness. Our results are surprising because thicker light-sheets that provide lower image contrast have previously not been associated with better axial resolution. We conclude that classical Gaussian illumination beams should be used when image contrast is most important, and more advanced types of illumination represent a way to optimize axial resolution at the expense of image contrast.

show abstract

Section: Discussionmentioning

confidence: 99%

How to define and optimize axial resolution in light-sheet microscopy: a simulation-based approach

Remacha¹,

Friedrich²,

Vermot³

et al. 2019

Biomed. Opt. Express

View full text Add to dashboard Cite

show abstract

“…Other, more complex, illumination and detection schemes are suitable improve axial resolution and optical sectioning at the same time. Examples include structured illumination [14], confocal slit detection [15], STED, RESOLFT [30], tiling [31], axially scanned light sheets [32] and computational reconstruction of images acquired with complementary light sheets [33,34]. However, the improved performance comes at a cost such as, for example, excess light exposure or reduction in achievable imaging speed.…”

Section: Discussionmentioning

confidence: 99%

How to define and optimize axial resolution in light-sheet microscopy: a simulation-based approach

Remacha

Friedrich²,

Vermot

et al. 2019

Preprint

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How thick is your light sheet?" is a question that has been asked frequently after talks showing impressive renderings of 3D data acquired by a light-sheet microscope. This question is motivated by the fact that most of the time the thickness of the light-sheet is uniquely associated to the axial resolution of the microscope. However, the link between lightsheet thickness and axial resolution has never been systematically assessed and it is still unclear how both are connected. The question is not trivial because commonly employed measures cannot readily be applied or do not lead to easily interpretable results for the many different types of light sheet. Here, by using simulation data we introduce a set of intuitive measures that helps to define the relationship between light sheet thickness and axial resolution. Unexpectedly, our analysis revealed a trade-off between better axial resolution and thinner light-sheet thickness. Our results are surprising because thicker light-sheets that provide lower image contrast have previously not been associated with better axial resolution. We conclude that classical Gaussian illumination beams should be used when image contrast is most important, and more advanced types of illumination represent a way to optimize axial resolution at the expense of image contrast.

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“…[ 178,179 ] This technique holds potential in the axial and depth visualization of organisms, like zebrafish. [ 180 ] Factors, like hardware, probes, algorithm, interact with each other and play an important role in enhancing the axial the resolution and reducing the background noise.…”

Section: Methods For Improving Srimentioning

confidence: 99%

Resolution Enhancement and Background Suppression in Optical Super‐Resolution Imaging for Biological Applications

Wang

et al. 2020

Laser & Photonics Reviews

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For decades, the spatial resolution of conventional far‐field optical imaging has been constrained due to the diffraction limit. The emergence of optical super‐resolution imaging has facilitated biological research in the nanoscale regime. However, the existing super‐resolution modalities are not feasible in many biological applications due to weaknesses, like complex implementation and high cost. Recently, various newly proposed techniques are advantageous in the enhancement of the system resolution, background suppression, and improvement of the hardware complexity so that the above‐mentioned issues could be addressed. Most of these techniques entail the modification of factors, like hardware, light path, fluorescent probe, and algorithm, based on conventional imaging systems. Particularly, subtraction technique is an easily implemented, cost‐effective, and flexible imaging tool which has been applied in widespread utilizations. In this review, the principles, characteristics, advances, and biological applications of these techniques are highlighted in optical super‐resolution modalities.

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Axial resolution enhancement for light sheet fluorescence microscopy via using the subtraction method

Cited by 8 publications

References 21 publications

How to define and optimize axial resolution in light-sheet microscopy: a simulation-based approach

How to define and optimize axial resolution in light-sheet microscopy: a simulation-based approach

How to define and optimize axial resolution in light-sheet microscopy: a simulation-based approach

Resolution Enhancement and Background Suppression in Optical Super‐Resolution Imaging for Biological Applications

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