Design of a high-resolution light field miniscope for volumetric imaging in scattering tissue

Chen, Yanqin; Xiong, Bo; Xue, Yujia; Jin, Xin; Greene, Joseph; Tian, Lei

doi:10.1364/boe.384673

Cited by 21 publications

(15 citation statements)

References 36 publications

(72 reference statements)

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“…The final stage after correcting noise and shifts is the process of identifying the activity of neurons [26]. Currently, improvement of image processing algorithms and reduction of noises in data gotten during experiments are in work [8].…”

Section: Extraction Of Neural Activitymentioning

confidence: 99%

Possibilities of using a miniature fluorescence microscope

et al. 2020

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The article discusses an approach to fluorescence microscopy using single-photon miniature fluorescence microscopes. The use of miniscopes allows you to expand the possibilities of their usage and solve many problems related to the need of fixing experimental material, insufficient scanning speed, complexity and high cost of usage. The authors developed a unique algorithm of correlations building based on cross-correlation of neuronal signals and implemented the opportunity to import experiment’s data in csv format. (as well as a utility for converting data from CNMF-E), which allows to import data from other sources. Special attention is paid to the methods of processing neural activity data: filtering the received frames from noise, compensating of image shifts and distortions.

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Section: Extraction Of Neural Activitymentioning

confidence: 99%

Possibilities of using a miniature fluorescence microscope

et al. 2020

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“…Especially, the LF imaging method based on the wave-optics model and LF point spread function (LFPSF) allows 3D deconvolution for the high-quality single-shot volumetric reconstruction [6,7] . However, in some applications of LF imaging, a scattering medium is present in the scenes, such as biological tissue, fog, and turbid water [8][9][10][11][12][13][14][15][16] . In these imaging scenes, signal light could still be captured, and 3D reconstruction could be conducted, but scattered light produced by the scattering medium introduces blur and scattering background artifacts to the 3D reconstruction image, which lead to low resolution and low contrast.…”

Section: Introductionmentioning

confidence: 99%

Deep learning-based scattering removal of light field imaging

et al. 2022

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Light field imaging has shown significance in research fields for its high-temporal-resolution 3D imaging ability. However, in scenes of light field imaging through scattering, such as biological imaging in vivo and imaging in fog, the quality of 3D reconstruction will be severely reduced due to the scattering of the light field information. In this paper, we propose a deep learning-based method of scattering removal of light field imaging. In this method, a neural network, trained by simulation samples that are generated by light field imaging forward models with and without scattering, is utilized to remove the effect of scattering on light fields captured experimentally. With the deblurred light field and the scattering-free forward model, 3D reconstruction with high resolution and high contrast can be realized. We demonstrate the proposed method by using it to realize high-quality 3D reconstruction through a single scattering layer experimentally.

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“…Unlike systems designed to acquire 3D information by attaching an MLA to an existing microscope ( 17 – 19 ) or miniscope ( 13 , 27 ), the CM 2 uses the MLA as the sole imaging element ( Fig. 1, A and B ), allowing our setup to circumvent the FOV limitations imposed by the conventional objective lens ( 17 , 18 ) or the gradient index (GRIN) lens ( 13 , 27 ). In addition, this configuration offers a simple and compact form factor by removing the bulk of infinite-conjugate optics used in existing miniscopes ( 11 , 13 ).…”

Section: Introductionmentioning

confidence: 99%

Single-shot 3D wide-field fluorescence imaging with a Computational Miniature Mesoscope

et al. 2020

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Fluorescence microscopes are indispensable to biology and neuroscience. The need for recording in freely behaving animals has further driven the development in miniaturized microscopes (miniscopes). However, conventional microscopes/miniscopes are inherently constrained by their limited space-bandwidth product, shallow depth of field (DOF), and inability to resolve three-dimensional (3D) distributed emitters. Here, we present a Computational Miniature Mesoscope (CM2) that overcomes these bottlenecks and enables single-shot 3D imaging across an 8 mm by 7 mm field of view and 2.5-mm DOF, achieving 7-μm lateral resolution and better than 200-μm axial resolution. The CM2 features a compact lightweight design that integrates a microlens array for imaging and a light-emitting diode array for excitation. Its expanded imaging capability is enabled by computational imaging that augments the optics by algorithms. We experimentally validate the mesoscopic imaging capability on 3D fluorescent samples. We further quantify the effects of scattering and background fluorescence on phantom experiments.

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Design of a high-resolution light field miniscope for volumetric imaging in scattering tissue

Cited by 21 publications

References 36 publications

Possibilities of using a miniature fluorescence microscope

Possibilities of using a miniature fluorescence microscope

Deep learning-based scattering removal of light field imaging

Single-shot 3D wide-field fluorescence imaging with a Computational Miniature Mesoscope

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