Attenuation artifacts in light sheet fluorescence microscopy corrected by OPTiSPIM

Mayer, J.; Robert‐Moreno, Alexandre; Sharpe, James; Swoger, Jim

doi:10.1038/s41377-018-0068-z

Cited by 28 publications

(19 citation statements)

References 48 publications

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“…In widefield or spinning disk confocal microscopes 63 , uneven detection efficiency often requires non-uniformity correction. In the case of mesoscale light-sheet microscopy, the problem is far more complex because illumination shadows are caused by sampleinduced occlusion 64 . We believe that CNNs are well positioned to address this problem.…”

Section: Box 3 Deep Learning As Differential Learningmentioning

confidence: 99%

Applications, Promises, and Pitfalls of Deep Learning for Fluorescence Image Reconstruction

Belthangady¹,

Royer²

2019

Preprint

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Deep Learning is a recent and important addition to the computational toolbox available for image reconstruction in fluorescence microscopy. We review state-of-the-art applications such as image restoration, super-resolution, and light-field imaging, and discuss how the latest Deep Learning research can be applied to other image reconstruction tasks such as structured illumination, spectral deconvolution, and sample stabilisation. Despite its successes, Deep Learning also poses significant challenges, has often misunderstood capabilities, and overlooked limits. We will address key questions, such as: What are the challenges in obtaining training data? Can we discover structures not present in the training data? And, what is the danger of inferring unsubstantiated image details?

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Section: Box 3 Deep Learning As Differential Learningmentioning

confidence: 99%

Applications, Promises, and Pitfalls of Deep Learning for Fluorescence Image Reconstruction

Belthangady¹,

Royer²

2019

Preprint

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“…However, they are not well suited for SPIM microscopy, because their low spatial coherence limits the possibility to focus the light into a single plane. Here we show not only that LEDs can be used to optically section the sample, but also that the use of incoherent light can reduce the unwanted speckle pattern and shadowing effects typical of SPIM [5], being an alternative to methods shown in [6][7][8].…”

Section: Introductionmentioning

confidence: 90%

Spatially modulated illumination allows for light sheet fluorescence microscopy with an incoherent source and compressive sensing

Calisesi¹,

Castriotta²,

Candeo³

et al. 2019

Biomed. Opt. Express

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Light sheet fluorescence microscopy has become one of the most widely used techniques for three-dimensional imaging due to its high speed and low phototoxicity. Further improvements in 3D microscopy require limiting the light exposure of the sample and increasing the volumetric acquisition rate. We hereby present an imaging technique that allows volumetric reconstruction of the fluorescent sample using spatial modulation on a selective illumination volume. We demonstrate that this can be implemented using an incoherent LED source, avoiding shadowing artifacts, typical of light sheet microscopy. Furthermore, we show that spatial modulation allows the use of Compressive Sensing, reducing the number of modulation patterns to be acquired. We present results on zebrafish embryos which prove that selective spatial modulation can be used to reconstruct relatively large volumes without any mechanical movement. The technique yields an accurate reconstruction of the sample anatomy even at significant compression ratios, achieving higher volumetric acquisition rate and reducing photodamage biological samples.

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“…The exploited concept of RI matching between clearing solution, holder and tissue allowed them to image samples cleared with distinct protocols that span the entire RI range of already published methods (1.33–1.56) with up to 0.5 cm imaging depth. Yet another novel idea for improving the quality of LSFM‐obtained images, by solving the problem of typical artifacts (such as already mentioned striping artifacts), was presented by Mayer et al . By using already known hybrid system of two distinct imaging modalities: LSFM with optical projection tomography (called OPTiSPIM), the authors successfully combined LSFM‐derived high‐resolution fluorescence data with 3D maps of the attenuation to “refill” shadows/striping artifacts ( Figure ).…”

Section: Approaches To Tocmentioning

confidence: 99%

“…b,c) E12.5 embryonic mouse head before (b) and after (c) attenuation correction. Reproduced under the terms of the CC‐BY Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/) . Copyright 2018, The Authors.…”

Section: Approaches To Tocmentioning

confidence: 99%

Advances in Ex Situ Tissue Optical Clearing

Matryba

Kaczmarek

Gołąb

2019

Laser & Photonics Reviews

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Examination of whole organs with subcellular resolution in health, disease, and during development is necessary to decipher their biological complexity. However, until recently, this has been virtually impossible due to the natural opacity of organ tissue. Recent progress in tissue optical clearing (TOC) has overcome this limitation by turning organs into transparent, light-permitting specimens. At least 20 original TOC methods have been developed in less than a decade, which were followed by hundreds of attempts that were aimed at their optimization and practical application. The majority of proof-of-concept studies have focused on the brain. However, it is apparent that TOC might be equally valuable when applied to peripheral organs or even the whole body. The progress in TOC for peripheral organs is delineated in an organ-by-organ fashion and whole-body clearing approaches are discussed. Additionally, physical and optical approaches for TOC affecting the optical properties of the samples and image quality are discussed to explore their advantages, limitations, and future possibilities.

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Attenuation artifacts in light sheet fluorescence microscopy corrected by OPTiSPIM

Cited by 28 publications

References 48 publications

Applications, Promises, and Pitfalls of Deep Learning for Fluorescence Image Reconstruction

Applications, Promises, and Pitfalls of Deep Learning for Fluorescence Image Reconstruction

Spatially modulated illumination allows for light sheet fluorescence microscopy with an incoherent source and compressive sensing

Advances in Ex Situ Tissue Optical Clearing

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