High-resolution Fourier light-field microscopy for volumetric multi-color live-cell imaging

Spaceflight alters protein levels and gene expression associated with stress response and metabolic characteristics in human cardiac spheroids

Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC-CMs) possess tremendous advantage for cardiac regeneration. However, cell survival is challenging upon cell transplantation. Since microgravity can profoundly affect cellular properties, we investigated the effect of spaceflight on hiPSC-CMs. Cardiac spheroids derived from hiPSCs were transported to the International Space Station (ISS) via the SpaceX Crew-8 mission and cultured under space microgravity for 8 days. Beating cardiac spheroids were observed on the ISS and upon successful experimentation by the astronauts in space, the live cultures were returned to Earth. These cells had normal displacement (an indicator of contraction) and Ca2+ transient parameters in 3D live cell imaging. Proteomic analysis revealed that spaceflight upregulated many proteins involved in metabolism (n = 90), cellular component of mitochondrion (n = 62) and regulation of proliferation (n = 10). Specific metabolic pathways enriched by spaceflight included glutathione metabolism, biosynthesis of amino acids, and pyruvate metabolism. In addition, the top upregulated proteins in spaceflight samples included those involved in cellular stress response, cell survival, and metabolism. Transcriptomic profiles indicated that spaceflight upregulated genes associated with cardiomyocyte development, and cellular components of cardiac structure and mitochondrion. Furthermore, spaceflight upregulated genes in metabolic pathways associated with cell survival such as glycerophospholipid metabolism and glycerolipid metabolism. These findings indicate that short-term exposure of 3D hiPSC-CMs to the space environment led to significant changes in protein levels and gene expression involved in cell survival and metabolism.

Lipid nanoparticle-mediated mRNA delivery to CD34+ cells in rhesus monkeys

Transplantation of ex vivo engineered hematopoietic stem cells (HSCs) can lead to robust clinical responses but carries risks of adverse events from bone marrow mobilization, chemotherapy conditioning and other factors. HSCs have been modified in vivo using lipid nanoparticles (LNPs) decorated with targeting moieties, which increases manufacturing complexity. Here we screen 105 LNPs without targeting ligands for effective homing to the bone marrow in mouse. We report an LNP named LNP67 that delivers mRNA to murine HSCs in vivo, primary human HSCs ex vivo and CD34+ cells in rhesus monkeys (Macaca mulatta) in vivo at doses of 0.25 and 0.4 mg kg-1. Without mobilization and conditioning, LNP67 can mediate delivery of mRNA to HSCs and their progenitor cells (HSPCs), as well as to the liver in rhesus monkeys, without serum cytokine activation. These data support the hypothesis that in vivo delivery to HSCs and HSPCs in nonhuman primates is feasible without targeting ligands.

Volumetric imaging and computation to explore contractile function in zebrafish hearts

Despite advancements in cardiovascular engineering, heart diseases remain a leading cause of mortality. The limited understanding of the underlying mechanisms of cardiac dysfunction at the cellular level restricts the development of effective screening and therapeutic methods. To address this, we have developed a framework that incorporates light field detection and individual cell tracking to capture real-time volumetric data in zebrafish hearts, which share structural and electrical similarities with the human heart and generate 120 to 180 beats per minute. Our results indicate that the in-house system achieves an acquisition speed of 200 volumes per second, with resolutions of up to 5.02 ± 0.54 µm laterally and 9.02 ± 1.11 µm axially across the entire depth, using the estimated-maximized-smoothed deconvolution method. The subsequent deep learning-based cell trackers enable further investigation of contractile dynamics, including cellular displacement and velocity, followed by volumetric tracking of specific cells of interest from end-systole to end-diastole in an interactive environment. Collectively, our strategy facilitates real-time volumetric imaging and assessment of contractile dynamics across the entire ventricle at the cellular resolution over multiple cycles, providing significant potential for exploring intercellular interactions in both health and disease.

Fourier Raman light field microscopy based on surface-enhanced Raman scattering

Raman scattering, as a vibrational spectrum that carries material information, has no photobleaching that enables long-duration imaging. Raman spectra have very narrow emission peaks, and multiplex Raman imaging can be achieved by using different Raman scattering peak signals. These advantages make Raman imaging widely used in biology, cytology, and medicine, which has a wider range of application scenarios. However, obtaining a three-dimensional (3D) Raman image requires scanning for tens of minutes to several hours at present. Therefore, a fast non-scanning 3D Raman imaging method is greatly needed. In this article, we propose a Fourier Raman light field microscopy based on surface-enhanced Raman scattering (sers-FRLFM). Using flower-like gap-enhanced Raman nanoparticles (F-GERNs) to enhance Raman scattering signals, a Fourier-configured light field microscope (LFM) is capable of recording complete four-dimensional Raman field information in a single frame, facilitating the 3D reconstruction of the Raman image without generating reconstruction artifacts at the native object plan. Moreover, F-GERNs can mark specific locations and have the potential to become a new tracing method to achieve specific imaging. This imaging method has great potential in the 3D real-time Raman imaging of cells, microorganisms, and tissues with the lateral resolution of 2.40 µm and an axial resolution of 4.02 µm.

Wide-field, high-resolution reconstruction in computational multi-aperture miniscope using a Fourier neural network

Traditional fluorescence microscopy is constrained by inherent trade-offs among resolution, field of view, and system complexity. To navigate these challenges, we introduce a simple and low-cost computational multi-aperture miniature microscope, utilizing a microlens array for single-shot wide-field, high-resolution imaging. Addressing the challenges posed by extensive view multiplexing and non-local, shift-variant aberrations in this device, we present SV-FourierNet, a multi-channel Fourier neural network. SV-FourierNet facilitates high-resolution image reconstruction across the entire imaging field through its learned global receptive field. We establish a close relationship between the physical spatially varying point-spread functions and the network's learned effective receptive field. This ensures that SV-FourierNet has effectively encapsulated the spatially varying aberrations in our system and learned a physically meaningful function for image reconstruction. Training of SV-FourierNet is conducted entirely on a physics-based simulator. We showcase wide-field, high-resolution video reconstructions on colonies of freely moving C. elegans and imaging of a mouse brain section. Our computational multi-aperture miniature microscope, augmented with SV-FourierNet, represents a major advancement in computational microscopy and may find broad applications in biomedical research and other fields requiring compact microscopy solutions.

Efficient high-resolution fluorescence projection imaging over an extended depth of field through optical hardware and deep learning optimizations

Optical microscopy has witnessed notable advancements but has also become more costly and complex. Conventional wide field microscopy (WFM) has low resolution and shallow depth-of-field (DOF), which limits its applications in practical biological experiments. Recently, confocal and light sheet microscopy become major workhorses for biology that incorporate high-precision scanning to perform imaging within an extended DOF but at the sacrifice of expense, complexity, and imaging speed. Here, we propose deep focus microscopy, an efficient framework optimized both in hardware and algorithm to address the tradeoff between resolution and DOF. Our deep focus microscopy achieves large-DOF and high-resolution projection imaging by integrating a deep focus network (DFnet) into light field microscopy (LFM) setups. Based on our constructed dataset, deep focus microscopy features a significantly enhanced spatial resolution of ∼260 nm, an extended DOF of over 30 µm, and broad generalization across diverse sample structures. It also reduces the computational costs by four orders of magnitude compared to conventional LFM technologies. We demonstrate the excellent performance of deep focus microscopy in vivo, including long-term observations of cell division and migrasome formation in zebrafish embryos and mouse livers at high resolution without background contamination.

Long-term intravital subcellular imaging with confocal scanning light-field microscopy

Long-term observation of subcellular dynamics in living organisms is limited by background fluorescence originating from tissue scattering or dense labeling. Existing confocal approaches face an inevitable tradeoff among parallelization, resolution and phototoxicity. Here we present confocal scanning light-field microscopy (csLFM), which integrates axially elongated line-confocal illumination with the rolling shutter in scanning light-field microscopy (sLFM). csLFM enables high-fidelity, high-speed, three-dimensional (3D) imaging at near-diffraction-limit resolution with both optical sectioning and low phototoxicity. By simultaneous 3D excitation and detection, the excitation intensity can be reduced below 1 mW mm-2, with 15-fold higher signal-to-background ratio over sLFM. We imaged subcellular dynamics over 25,000 timeframes in optically challenging environments in different species, such as migrasome delivery in mouse spleen, retractosome generation in mouse liver and 3D voltage imaging in Drosophila. Moreover, csLFM facilitates high-fidelity, large-scale neural recording with reduced crosstalk, leading to high orientation selectivity to visual stimuli, similar to two-photon microscopy, which aids understanding of neural coding mechanisms.

Cationic cholesterol-dependent LNP delivery to lung stem cells, the liver, and heart

Adding a cationic helper lipid to a lipid nanoparticle (LNP) can increase lung delivery and decrease liver delivery. However, it remains unclear whether charge-dependent tropism is universal or, alternatively, whether it depends on the component that is charged. Here, we report evidence that cationic cholesterol-dependent tropism can differ from cationic helper lipid-dependent tropism. By testing how 196 LNPs delivered mRNA to 22 cell types, we found that charged cholesterols led to a different lung:liver delivery ratio than charged helper lipids. We also found that combining cationic cholesterol with a cationic helper lipid led to mRNA delivery in the heart as well as several lung cell types, including stem cell-like populations. These data highlight the utility of exploring charge-dependent LNP tropism.

Light-field flow cytometry for high-resolution, volumetric and multiparametric 3D single-cell analysis

Imaging flow cytometry (IFC) combines flow cytometry and fluorescence microscopy to enable high-throughput, multiparametric single-cell analysis with rich spatial details. However, current IFC techniques remain limited in their ability to reveal subcellular information with a high 3D resolution, throughput, sensitivity, and instrumental simplicity. In this study, we introduce a light-field flow cytometer (LFC), an IFC system capable of high-content, single-shot, and multi-color acquisition of up to 5,750 cells per second with a near-diffraction-limited resolution of 400-600 nm in all three dimensions. The LFC system integrates optical, microfluidic, and computational strategies to facilitate the volumetric visualization of various 3D subcellular characteristics through convenient access to commonly used epi-fluorescence platforms. We demonstrate the effectiveness of LFC in assaying, analyzing, and enumerating intricate subcellular morphology, function, and heterogeneity using various phantoms and biological specimens. The advancement offered by the LFC system presents a promising methodological pathway for broad cell biological and translational discoveries, with the potential for widespread adoption in biomedical research.

Fast light-field 3D microscopy with out-of-distribution detection and adaptation through conditional normalizing flows

Real-time 3D fluorescence microscopy is crucial for the spatiotemporal analysis of live organisms, such as neural activity monitoring. The eXtended field-of-view light field microscope (XLFM), also known as Fourier light field microscope, is a straightforward, single snapshot solution to achieve this. The XLFM acquires spatial-angular information in a single camera exposure. In a subsequent step, a 3D volume can be algorithmically reconstructed, making it exceptionally well-suited for real-time 3D acquisition and potential analysis. Unfortunately, traditional reconstruction methods (like deconvolution) require lengthy processing times (0.0220 Hz), hampering the speed advantages of the XLFM. Neural network architectures can overcome the speed constraints but do not automatically provide a way to certify the realism of their reconstructions, which is essential in the biomedical realm. To address these shortcomings, this work proposes a novel architecture to perform fast 3D reconstructions of live immobilized zebrafish neural activity based on a conditional normalizing flow. It reconstructs volumes at 8 Hz spanning 512x512x96 voxels, and it can be trained in under two hours due to the small dataset requirements (50 image-volume pairs). Furthermore, normalizing flows provides a way to compute the exact likelihood of a sample. This allows us to certify whether the predicted output is in- or ood, and retrain the system when a novel sample is detected. We evaluate the proposed method on a cross-validation approach involving multiple in-distribution samples (genetically identical zebrafish) and various out-of-distribution ones.

High-resolution 3D imaging in light-field microscopy through Stokes matrices and data fusion

The trade-off between the lateral and vertical resolution has long posed challenges to the efficient and widespread application of Fourier light-field microscopy, a highly scalable 3D imaging tool. Although existing methods for resolution enhancement can improve the measurement result to a certain extent, they come with limitations in terms of accuracy and applicable specimen types. To address these problems, this paper proposed a resolution enhancement scheme utilizing data fusion of polarization Stokes vectors and light-field information for Fourier light-field microscopy system. By introducing the surface normal vector information obtained from polarization measurement and integrating it with the light-field 3D point cloud data, 3D reconstruction results accuracy is highly improved in axial direction. Experimental results with a Fourier light-field 3D imaging microscope demonstrated a substantial enhancement of vertical resolution with a depth resolution to depth of field ratio of 0.19%. This represented approximately 44 times the improvement compared to the theoretical ratio before data fusion, enabling the system to access more detailed information with finer measurement accuracy for test samples. This work not only provides a feasible solution for breaking the limitations imposed by traditional light-field microscope hardware configurations but also offers superior 3D measurement approach in a more cost-effective and practical manner.

Video-rate 3D imaging of living cells using Fourier view-channel-depth light field microscopy

Interrogation of subcellular biological dynamics occurring in a living cell often requires noninvasive imaging of the fragile cell with high spatiotemporal resolution across all three dimensions. It thereby poses big challenges to modern fluorescence microscopy implementations because the limited photon budget in a live-cell imaging task makes the achievable performance of conventional microscopy approaches compromise between their spatial resolution, volumetric imaging speed, and phototoxicity. Here, we incorporate a two-stage view-channel-depth (VCD) deep-learning reconstruction strategy with a Fourier light-field microscope based on diffractive optical element to realize fast 3D super-resolution reconstructions of intracellular dynamics from single diffraction-limited 2D light-filed measurements. This VCD-enabled Fourier light-filed imaging approach (F-VCD), achieves video-rate (50 volumes per second) 3D imaging of intracellular dynamics at a high spatiotemporal resolution of ~180 nm × 180 nm × 400 nm and strong noise-resistant capability, with which light field images with a signal-to-noise ratio (SNR) down to -1.62 dB could be well reconstructed. With this approach, we successfully demonstrate the 4D imaging of intracellular organelle dynamics, e.g., mitochondria fission and fusion, with ~5000 times of observation.

Optimal sparsity allows reliable system-aware restoration of fluorescence microscopy images

Fluorescence microscopy is one of the most indispensable and informative driving forces for biological research, but the extent of observable biological phenomena is essentially determined by the content and quality of the acquired images. To address the different noise sources that can degrade these images, we introduce an algorithm for multiscale image restoration through optimally sparse representation (MIRO). MIRO is a deterministic framework that models the acquisition process and uses pixelwise noise correction to improve image quality. Our study demonstrates that this approach yields a remarkable restoration of the fluorescence signal for a wide range of microscopy systems, regardless of the detector used (e.g., electron-multiplying charge-coupled device, scientific complementary metal-oxide semiconductor, or photomultiplier tube). MIRO improves current imaging capabilities, enabling fast, low-light optical microscopy, accurate image analysis, and robust machine intelligence when integrated with deep neural networks. This expands the range of biological knowledge that can be obtained from fluorescence microscopy.

Volumetric live-cell autofluorescence imaging using Fourier light-field microscopy

This study introduces a rapid, volumetric live-cell imaging technique for visualizing autofluorescent sub-cellular structures and their dynamics by employing high-resolution Fourier light-field microscopy. We demonstrated this method by capturing lysosomal autofluorescence in fibroblasts and HeLa cells. Additionally, we conducted multicolor imaging to simultaneously observe lysosomal autofluorescence and fluorescently-labeled organelles such as lysosomes and mitochondria. We further analyzed the data to quantify the interactions between lysosomes and mitochondria. This research lays the foundation for future exploration of native cellular states and functions in three-dimensional environments, effectively reducing photodamage and eliminating the necessity for exogenous labels.

3D Chemical Imaging by Fluorescence-detected Mid-Infrared Photothermal Fourier Light Field Microscopy

Three-dimensional molecular imaging of living organisms and cells plays a significant role in modern biology. Yet, current volumetric imaging modalities are largely fluorescence-based and thus lack chemical content information. Mid-infrared photothermal microscopy as a chemical imaging technology provides infrared spectroscopic information at submicrometer spatial resolution. Here, by harnessing thermosensitive fluorescent dyes to sense the mid-infrared photothermal effect, we demonstrate 3D fluorescence-detected mid-infrared photothermal Fourier light field (FMIP-FLF) microscopy at the speed of 8 volumes per second and submicron spatial resolution. Protein contents in bacteria and lipid droplets in living pancreatic cancer cells are visualized. Altered lipid metabolism in drug-resistant pancreatic cancer cells is observed with the FMIP-FLF microscope.

Practical guide for setting up a Fourier light-field microscope

A practical guide for the easy implementation of a Fourier light-field microscope is reported. The Fourier light-field concept applied to microscopy allows the capture in real time of a series of 2D orthographic images of microscopic thick dynamic samples. Such perspective images contain spatial and angular information of the light-field emitted by the sample. A feature of this technology is the tight requirement of a double optical conjugation relationship, and also the requirement of NA matching. For these reasons, the Fourier light-field microscope being a non-complex optical system, a clear protocol on how to set up the optical elements accurately is needed. In this sense, this guide is aimed to simplify the implementation process, with an optical bench and off-the-shelf components. This will help the widespread use of this recent technology.

Compact, Hybrid Light-Sheet and Fourier Light-Field Microscopy with a Single Objective for High-Speed Volumetric Imaging In Vivo

Volumetric imaging of biodynamics at high spatiotemporal resolutions in vivo is vital in biomedical studies, in which Fourier light field microscopy (FLFM) is a promising technique. However, the commonly used wide-field illumination strategy in FLFM introduces intense out of depth-of-field background, which not only degrades the image quality, but also introduces reconstruction artifacts. Employing light sheet illumination is an effective way to alleviate the background and reduce photobleaching in light-field microscopy. Unfortunately, the introduction of light-sheet illumination often requires an extra objective and precise alignment, which increases the system complexity. Here, we propose the compact, hybrid light-sheet and FLFM (CLS-FLFM), which uses only a single objective to achieve both light-sheet illumination and Fourier light-field imaging simultaneously. With a micromirror under the objective, we focus the light sheet, which ensures selective-volume-illumination, on the imaging plane of the FLFM to perform volumetric imaging. We demonstrate the superior performance of CLS-FLFM in inhibiting background in both structural and dynamical imaging of larval zebrafish in vivo. We envision that CLS-FLFM finds wide applications in high-speed, background-inhibited volumetric imaging of biodynamics in vivo.

Volumetric imaging of fast cellular dynamics with deep learning enhanced bioluminescence microscopy

Bioluminescence microscopy is an appealing alternative to fluorescence microscopy, because it does not depend on external illumination, and consequently does neither produce spurious background autofluorescence, nor perturb intrinsically photosensitive processes in living cells and animals. The low photon emission of known luciferases, however, demands long exposure times that are prohibitive for imaging fast biological dynamics. To increase the versatility of bioluminescence microscopy, we present an improved low-light microscope in combination with deep learning methods to image extremely photon-starved samples enabling subsecond exposures for timelapse and volumetric imaging. We apply our method to image subcellular dynamics in mouse embryonic stem cells, epithelial morphology during zebrafish development, and DAF-16 FoxO transcription factor shuttling from the cytoplasm to the nucleus under external stress. Finally, we concatenate neural networks for denoising and light-field deconvolution to resolve intracellular calcium dynamics in three dimensions of freely moving Caenorhabditis elegans.

Volumetric Imaging of Neural Activity by Light Field Microscopy

Recording the highly diverse and dynamic activities in large populations of neurons in behaving animals is crucial for a better understanding of how the brain works. To meet this challenge, extensive efforts have been devoted to developing functional fluorescent indicators and optical imaging techniques to optically monitor neural activity. Indeed, optical imaging potentially has extremely high throughput due to its non-invasive access to large brain regions and capability to sample neurons at high density, but the readout speed, such as the scanning speed in two-photon scanning microscopy, is often limited by various practical considerations. Among different imaging methods, light field microscopy features a highly parallelized 3D fluorescence imaging scheme and therefore promises a novel and faster strategy for functional imaging of neural activity. Here, we briefly review the working principles of various types of light field microscopes and their recent developments and applications in neuroscience studies. We also discuss strategies and considerations of optimizing light field microscopy for different experimental purposes, with illustrative examples in imaging zebrafish and mouse brains.

3D super-resolution live-cell imaging with radial symmetry and Fourier light-field microscopy

Live-cell imaging reveals the phenotypes and mechanisms of cellular function and their dysfunction that underscore cell physiology, development, and pathology. Here, we report a 3D super-resolution live-cell microscopy method by integrating radiality analysis and Fourier light-field microscopy (rad-FLFM). We demonstrated the method using various live-cell specimens, including actins in Hela cells, microtubules in mammary organoid cells, and peroxisomes in COS-7 cells. Compared with conventional wide-field microscopy, rad-FLFM realizes scanning-free, volumetric 3D live-cell imaging with sub-diffraction-limited resolution of ∼150 nm (x-y) and 300 nm (z), milliseconds volume acquisition time, six-fold extended depth of focus of ∼6 µm, and low photodamage. The method provides a promising avenue to explore spatiotemporal-challenging subcellular processes in a wide range of cell biological research.

Background inhibited and speed-loss-free volumetric imaging in vivo based on structured-illumination Fourier light field microscopy

Benefiting from its advantages in fast volumetric imaging for recording biodynamics, Fourier light field microscopy (FLFM) has a wide range of applications in biomedical research, especially in neuroscience. However, the imaging quality of the FLFM is always deteriorated by both the out-of-focus background and the strong scattering in biological samples. Here we propose a structured-illumination and interleaved-reconstruction based Fourier light field microscopy (SI-FLFM), in which we can filter out the background fluorescence in FLFM without sacrificing imaging speed. We demonstrate the superiority of our SI-FLFM in high-speed, background-inhibited volumetric imaging of various biodynamics in larval zebrafish and mice in vivo. The signal-to-background ratio (SBR) is improved by tens of times. And the volumetric imaging speed can be up to 40 Hz, avoiding artifacts caused by temporal under-sampling in conventional structured illumination microscopy. These suggest that our SI-FLFM is suitable for applications of weak fluorescence signals but high imaging speed requirements.

Deep-learning-augmented computational miniature mesoscope

Fluorescence microscopy is essential to study biological structures and dynamics. However, existing systems suffer from a trade-off between field of view (FOV), resolution, and system complexity, and thus cannot fulfill the emerging need for miniaturized platforms providing micron-scale resolution across centimeter-scale FOVs. To overcome this challenge, we developed a computational miniature mesoscope (CM2) that exploits a computational imaging strategy to enable single-shot, 3D high-resolution imaging across a wide FOV in a miniaturized platform. Here, we present CM2 V2, which significantly advances both the hardware and computation. We complement the 3 × 3 microlens array with a hybrid emission filter that improves the imaging contrast by 5×, and design a 3D-printed free-form collimator for the LED illuminator that improves the excitation efficiency by 3×. To enable high-resolution reconstruction across a large volume, we develop an accurate and efficient 3D linear shift-variant (LSV) model to characterize spatially varying aberrations. We then train a multimodule deep learning model called CM2Net, using only the 3D-LSV simulator. We quantify the detection performance and localization accuracy of CM2Net to reconstruct fluorescent emitters under different conditions in simulation. We then show that CM2Net generalizes well to experiments and achieves accurate 3D reconstruction across a ~7-mm FOV and 800-μm depth, and provides ~6-μm lateral and ~25-μm axial resolution. This provides an ~8× better axial resolution and ~1400× faster speed compared to the previous model-based algorithm. We anticipate this simple, low-cost computational miniature imaging system will be useful for many large-scale 3D fluorescence imaging applications.

Single-Shot Light-Field Microscopy: An Emerging Tool for 3D Biomedical Imaging

3D microscopy is a useful tool to visualize the detailed structures and mechanisms of biomedical specimens. In particular, biophysical phenomena such as neural activity require fast 3D volumetric imaging because fluorescence signals degrade quickly. A light-field microscope (LFM) has recently attracted attention as a high-speed volumetric imaging technique by recording 3D information in a single-snapshot. This review highlighted recent progress in LFM techniques for 3D biomedical applications. In detail, various image reconstruction algorithms according to LFM configurations are explained, and several biomedical applications such as neuron activity localization, live-cell imaging, locomotion analysis, and single-molecule visualization are introduced. We also discuss deep learning-based LFMs to enhance image resolution and reduce reconstruction artifacts.

Fourier light-field imaging of human organoids with a hybrid point-spread function

Volumetric interrogation of the cellular morphology and dynamic processes of organoid systems with a high spatiotemporal resolution provides critical insights for understanding organogenesis, tissue homeostasis, and organ function. Fluorescence microscopy has emerged as one of the most vital and informative driving forces for probing the cellular complexity in organoid research. However, the underlying scanning mechanism of conventional imaging methods inevitably compromises the time resolution of volumetric acquisition, leading to increased photodamage and inability to capture fast cellular and tissue dynamic processes. Here, we report Fourier light-field microscopy using a hybrid point-spread function (hPSF-FLFM) for fast, volumetric, and high-resolution imaging of entire organoids. hPSF-FLFM transforms conventional 3D microscopy and enables exploration of less accessible spatiotemporally-challenging regimes for organoid research. To validate hPSF-FLFM, we demonstrate 3D imaging of rapid responses to extracellular physical cues such as osmotic and mechanical stresses on human induced pluripotent stem cells-derived colon organoids (hCOs). The system offers cellular (2-3 μm and 5-6 μm in x-y and z, respectively) and millisecond-scale spatiotemporal characterization of whole-organoid dynamic changes that span large imaging volumes (>900 μm × 900 μm × 200 μm in x, y, z, respectively). The hPSF-FLFM method provides a promising avenue to explore spatiotemporal-challenging cellular responses in a wide variety of organoid research.

Machine Learning-Based View Synthesis in Fourier Lightfield Microscopy

Current interest in Fourier lightfield microscopy is increasing, due to its ability to acquire 3D images of thick dynamic samples. This technique is based on simultaneously capturing, in a single shot, and with a monocular setup, a number of orthographic perspective views of 3D microscopic samples. An essential feature of Fourier lightfield microscopy is that the number of acquired views is low, due to the trade-off relationship existing between the number of views and their corresponding lateral resolution. Therefore, it is important to have a tool for the generation of a high number of synthesized view images, without compromising their lateral resolution. In this context we investigate here the use of a neural radiance field view synthesis method, originally developed for its use with macroscopic scenes acquired with a moving (or an array of static) digital camera(s), for its application to the images acquired with a Fourier lightfield microscope. The results obtained and presented in this paper are analyzed in terms of lateral resolution and of continuous and realistic parallax. We show that, in terms of these requirements, the proposed technique works efficiently in the case of the epi-illumination microscopy mode.

Fourier lightfield microscopy: a practical design guide

In this work, a practical guide for the design of a Fourier lightfield microscope is reported. The fundamentals of the Fourier lightfield are presented and condensed on a set of contour plots from which the user can select the design values of the spatial resolution, the field of view, and the depth of field, as function of the specifications of the hardware of the host microscope. This work guides the reader to select the parameters of the infinity-corrected microscope objective, the optical relay lenses, the aperture stop, the microlens array, and the digital camera. A user-friendly graphic calculator is included to ease the design, even to those who are not familiar with the lightfield technology. The guide is aimed to simplify the design process of a Fourier lightfield microscope, which sometimes could be a daunting task, and in this way, to invite the widespread use of this technology. An example of a design and experimental results on imaging different types of samples is also presented.

Handheld and Cost-Effective Fourier Lightfield Microscope

In this work, the design, building, and testing of the most portable, easy-to-build, robust, handheld, and cost-effective Fourier Lightfield Microscope (FLMic) to date is reported. The FLMic is built by means of a surveillance camera lens and additional off-the-shelf optical elements, resulting in a cost-effective FLMic exhibiting all the regular sought features in lightfield microscopy, such as refocusing and gathering 3D information of samples by means of a single-shot approach. The proposed FLMic features reduced dimensions and light weight, which, combined with its low cost, turn the presented FLMic into a strong candidate for in-field application where 3D imaging capabilities are pursued. The use of cost-effective optical elements has a relatively low impact on the optical performance, regarding the figures dictated by the theory, while its price can be at least 100 times lower than that of a regular FLMic. The system operability is tested in both bright-field and fluorescent modes by imaging a resolution target, a honeybee wing, and a knot of dyed cotton fibers.