In complex media such as white paint and biological tissue, light encounters nanoscale refractive-index inhomogeneities that cause multiple scattering. Such scattering is usually seen as an impediment to focusing and imaging. However, scientists have recently used strongly scattering materials to focus, shape and compress waves by controlling the many degrees of freedom in the incident waves. This was first demonstrated in the acoustic and microwave domains using time reversal, and is now being performed in the optical realm using spatial light modulators to address the many thousands of spatial degrees of freedom of light. This approach is being used to investigate phenomena such as optical super-resolution and the time reversal of light, thus opening many new avenues for imaging and focusing in turbid media

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Controlling waves in space and time for imaging and focusing in complex media

The resolution of an optical microscope is fundamentally limited by diffraction. In a conventional wide-field fluorescence microscope, the resolution limit is at best 200 nm. However, modern superresolution methods can bypass this limit. Pointillistic imaging techniques like PALM (photoactivated localization microscopy) and STORM (stochastic optical reconstruction microscopy) do so by precisely localizing each individual molecule in a sample. In contrast, STED uses the stimulated emission process driven to saturation to dramatically reduce the size of the region in the sample that is capable of spontaneously emitting fluorescence. Structured illumination microscopy (SIM) illuminates the sample with a pattern, typically the image of a grating. This computationally removes the out-of-focus blur, a method known as optical sectioning SIM. Furthermore, frequency mixing of the illumination pattern with the sample caused by the moire effect results in a downmodulation of fine sample detail into the frequency-sup...

Superresolution Multidimensional Imaging with Structured Illumination Microscopy

A device and method for performing fluorescence imaging with digitally time reversed ultrasound encoded light, using a source of ultrasound waves, a coherent light source, a digital optical phase conjugation (DOPC) device comprising a camera and a spatial light modulator (SLM), a detector of fluorescence, and one or more computers, to obtain an output that at least approximates an interaction between a complete time reversed field, of all of the encoded light's fields, and the scattering medium.

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Deep tissue focal fluorescence imaging with digitally time-reversed ultrasound-encoded light

Deep learning is becoming an increasingly important tool for image reconstruction in fluorescence microscopy. We review state-of-the-art applications such as image restoration and super-resolution imaging, and discuss how the latest deep learning research could be applied to other image reconstruction tasks. Despite its successes, deep learning also poses substantial challenges and has limits. We discuss key questions, including how to obtain training data, whether discovery of unknown structures is possible, and the danger of inferring unsubstantiated image details.

Applications, promises, and pitfalls of deep learning for fluorescence image reconstruction

Super-resolved structured illumination microscopy (SR-SIM) is an important tool for fluorescence microscopy. SR-SIM microscopes perform multiple image acquisitions with varying illumination patterns, and reconstruct them to a super-resolved image. In its most frequent, linear implementation, SR-SIM doubles the spatial resolution. The reconstruction is performed numerically on the acquired wide-field image data, and thus relies on a software implementation of specific SR-SIM image reconstruction algorithms. We present fairSIM, an easy-to-use plugin that provides SR-SIM reconstructions for a wide range of SR-SIM platforms directly within ImageJ. For research groups developing their own implementations of super-resolution structured illumination microscopy, fairSIM takes away the hurdle of generating yet another implementation of the reconstruction algorithm. For users of commercial microscopes, it offers an additional, in-depth analysis option for their data independent of specific operating systems. As a modular, open-source solution, fairSIM can easily be adapted, automated and extended as the field of SR-SIM progresses.

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Open-source image reconstruction of super-resolution structured illumination microscopy data in ImageJ

By illuminating a sample with several uncontrolled random speckles and implementing a blind structured illumination microscopy algorithm, researchers demonstrate that image reconstruction can be achieved without knowing the original illumination pattern, at a resolution two times better than that of conventional wide-field microscopy.

Structured illumination microscopy using unknown speckle patterns

Structured illumination microscopy (SIM) is a powerful technique for obtaining super-resolved fluorescence maps of samples, but it is very sensitive to aberrations or misalignments affecting the excitation patterns. Here, we present a reconstruction algorithm that is able to process SIM data even if the illuminations are strongly distorted. The approach is an extension of the recent blind-SIM technique, which reconstructs simultaneously the sample and the excitation patterns without a priori information on the latter. Our algorithm was checked on synthetic and experimental data using distorted and nondistorted illuminations. The reconstructions were similar to that obtained by up-to-date SIM methods when the illuminations were periodic and remained artifact-free when the illuminations were strongly distorted.

Structured illumination fluorescence microscopy with distorted excitations using a filtered blind-SIM algorithm

Focusing a light beam through a lens produces an anisotropic spot elongated along the optical axis, because the light comes from only one side of the focal point. Using the time-reversal concept, we show that isotropic focusing can be realized by placing a mirror after the focal point and shaping the incident beam. This idea is applied to confocal microscopy and brings about a dramatic improvement of the axial resolution.

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Isotropic diffraction-limited focusing using a single objective lens.

In microwave or optical wave imaging set-ups, the measured scattered field is usually not linearly linked to the target parameter of interest. To reconstruct the latter, nonlinearized or linearized iterative inversion techniques, such as the contrast source inversion method (CSI) or the conjugate gradient method (CGM) have been proposed (Litman and Crocco 2009 Inverse Problems 25 020201–5). In this paper, we adapt to the three-dimensional vectorial case, a hybrid method (HM) that combines the advantages of the CSI and CGM, and compare the performances of the different approaches using microwave experimental data. The HM appears to be the best compromise in terms of reconstruction accuracy, computation time and robustness to noise. (Some figures may appear in colour only in the online journal)

https://iopscience.iop.org/article/10.1088/0266-5611/28/6/065007/pdf

Electromagnetic wave imaging of three-dimensional targets using a hybrid iterative inversion method

We demonstrate that the axial resolution of a reflection tomographic diffractive microscope is drastically improved when the sample is placed in front of a perfect mirror. We show analytically and with rigorous simulations that this approach permits us to obtain images with the same isotropic resolution as that obtained when the sample is illuminated and observed from every possible angle. The main difficulty lies in accounting properly for the mirror in the inversion algorithm.

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Emeric Mudry

Papers

Structured illumination microscopy using unknown speckle patterns

Structured illumination fluorescence microscopy with distorted excitations using a filtered blind-SIM algorithm

Isotropic diffraction-limited focusing using a single objective lens.

Electromagnetic wave imaging of three-dimensional targets using a hybrid iterative inversion method

Mirror-assisted tomographic diffractive microscopy with isotropic resolution.