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Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However, for scientists wishing to publish obtained images and image-analysis results, there are currently no unified guidelines for best practices. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here, we present community-developed checklists for preparing light microscopy images and describing image analyses for publications. These checklists offer authors, readers and publishers key recommendations for image formatting and annotation, color selection, data availability and reporting image-analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby to heighten the quality and explanatory power of microscopy data.
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Lista de Verificación , Edición , Reproducibilidad de los Resultados , Procesamiento de Imagen Asistido por Computador , MicroscopíaRESUMEN
Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However for scientists wishing to publish the obtained images and image analyses results, there are to date no unified guidelines. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here we present community-developed checklists for preparing light microscopy images and image analysis for publications. These checklists offer authors, readers, and publishers key recommendations for image formatting and annotation, color selection, data availability, and for reporting image analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby heighten the quality and explanatory power of microscopy data is in publications.
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Random illumination microscopy (RIM) could surpass the diffraction barrier in fluorescence microscopy by illuminating an object with unknown speckle patterns. It has been demonstrated that the resolution in RIM using second-order statistics is as good as that of conventional structured illumination microscopy (SIM) from the asymptotic point of view. Compared to classical SIM, RIM is more robust to optical aberrations and scattering introduced by thick samples. In this work, I show that the quantum correlations could further improve the resolution in random illumination microscopy due to the photon antibunching property of fluorophore emitters. In theory, the super-resolution capacity of this quantum-enhanced version of RIM corresponds to the fourth power of the point spread function under the general epi-illumination geometry.
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[This retracts the article on p. 5147 in vol. 11, PMID: 33014605.].
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Random illumination microscopy (RIM) using uncontrolled speckle patterns has shown the capacity to surpass the Abbe's diffraction barrier, providing the possibility to design inexpensive and versatile structured illumination microscopy (SIM) devices. In this paper, I first present a review of the state-of-the-art joint reconstruction methods in RIM, and then propose a unified joint reconstruction approach in which the performance of various regularization terms can be evaluated under the same model. The model hyperparameter is easily tuned and robust in comparison to the previous methods and â2,1 regularizer is proven to be a reasonable prior in most practical situations. Moreover, the degradation entailed by out-of-focus light in conventional SIM can be easily solved in RIM setup.
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Photoacoustic (PA) imaging can provide information hidden deep inside biological tissues; however, its resolution is limited by acoustic diffraction. It has been demonstrated that the uncontrolled speckle illumination, which is known as blind structured illumination photoacoustic microscopy (BSIPAM), can help surpass this resolution barrier. Although the super-resolution capacity has been verified on both synthesized and experimental data, the achievable theoretical resolution limit by such a system is still unclear. This Letter shows that the principle of Stochastic Optical Reconstruction Microscopy (STORM) in a PA imaging system can be implemented by the tailored super-Rayleigh speckle; thus, a super-resolution better than a factor of two can be expected.
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The blind structured illumination microscopy strategy proposed by Mudry et al. is fully re-founded in this paper, unveiling the central role of the sparsity of the illumination patterns in the mechanism that drives super-resolution in the method. A numerical analysis shows that the resolving power of the method can be further enhanced with optimized one-photon or two-photon speckle illuminations. A much improved numerical implementation is provided for the reconstruction problem under the image positivity constraint. This algorithm rests on a new preconditioned proximal iteration faster than existing solutions, paving the way to 3D and real-time 2D reconstruction.