Mirror-enhanced scanning light-field microscopy for long-term high-speed 3D imaging with isotropic resolution

Ultrafast optical imaging techniques for exploring rapid neuronal dynamics

Optical neuroimaging has significantly advanced our understanding of brain function, particularly through techniques such as two-photon microscopy, which captures three-dimensional brain structures with sub-cellular resolution. However, traditional methods struggle to record fast, complex neuronal interactions in real time, which are crucial for understanding brain networks and developing treatments for neurological diseases such as Alzheimer's, Parkinson's, and chronic pain. Recent advancements in ultrafast imaging technologies, including kilohertz two-photon microscopy, light field microscopy, and event-based imaging, are pushing the boundaries of temporal resolution in neuroimaging. These techniques enable the capture of rapid neural events with unprecedented speed and detail. This review examines the principles, applications, and limitations of these technologies, highlighting their potential to revolutionize neuroimaging and improve the diagnose and treatment of neurological disorders. Despite challenges such as photodamage risks and spatial resolution trade-offs, integrating these approaches promises to enhance our understanding of brain function and drive future breakthroughs in neuroscience and medicine. Continued interdisciplinary collaboration is essential to fully leverage these innovations for advancements in both basic and clinical neuroscience.

Ultra-fast light-field microscopy with event detection

The event detection technique has been introduced to light-field microscopy, boosting its imaging speed in orders of magnitude with simultaneous axial resolution enhancement in scattering medium.

Extended-depth-of-field imaging with an ultra-thin folded lens

Optical systems with extended depth of field (EDOF) are crucial for observation and measurement applications, where achieving compactness and a substantial depth of field (DOF) presents a considerable challenge with conventional optical elements. In this paper, we propose an innovative solution for the miniaturization of EDOF imaging systems by introducing an ultra-thin annular folded lens (AFL). To validate the practical feasibility of the theory, we design an annular four-folded lens with an effective focal length of 80.91 mm and a total thickness of only 8.50 mm. Simulation results show that the proposed folded lens has a DOF of 380.55 m. We further developed an AFL-based test system exhibiting a resolution of 0.11 mrad across a wide wavelength range of 486-656 nm. Additionally, we present experimental results from a miniature compact prototype, which further highlights the promising potential of folded lenses for long-range EDOF imaging.

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.

Enhancing the color gamut of waveguide displays for augmented reality head-mounted displays through spatially modulated diffraction grating

Augmented reality (AR) applications require displays with an extended color gamut to facilitate the presentation of increasingly immersive content. The waveguide (WG) display technology, which is typical AR demonstration method, is a critical constraint on the color gamut of AR systems because of the intrinsic properties of the holographic optical elements (HOEs) used in this technology. To overcome this limitation, we introduce a method of spatially modulated diffractive optics that can expand the color gamut of HOE-based WG displays. This approach involves spatial modulation using sub-pixelized HOEs, which enables the diffraction of red, green, and blue rays along identical directions. The proposed structure considers both the characteristics of the HOE and the wavelength sensitivity of the observer to optimize the color gamut. Consequently, an expanded color gamut was achieved. The results of the theoretical and experimental analyses substantiate the effectiveness and practicality of this method in enhancing the color gamut of HOE-based WG displays. Thus, the proposed method can facilitate the implementation of more immersive AR displays.

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.

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.

AutoDeconJ: a GPU-accelerated ImageJ plugin for 3D light-field deconvolution with optimal iteration numbers predicting

MOTIVATION

Light-field microscopy (LFM) is a compact solution to high-speed 3D fluorescence imaging. Usually, we need to do 3D deconvolution to the captured raw data. Although there are deep neural network methods that can accelerate the reconstruction process, the model is not universally applicable for all system parameters. Here, we develop AutoDeconJ, a GPU-accelerated ImageJ plugin for 4.4× faster and more accurate deconvolution of LFM data. We further propose an image quality metric for the deconvolution process, aiding in automatically determining the optimal number of iterations with higher reconstruction accuracy and fewer artifacts.

RESULTS

Our proposed method outperforms state-of-the-art light-field deconvolution methods in reconstruction time and optimal iteration numbers prediction capability. It shows better universality of different light-field point spread function (PSF) parameters than the deep learning method. The fast, accurate and general reconstruction performance for different PSF parameters suggests its potential for mass 3D reconstruction of LFM data.

AVAILABILITY AND IMPLEMENTATION

The codes, the documentation and example data are available on an open source at: https://github.com/Onetism/AutoDeconJ.git.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

Noise-robust phase-space deconvolution for light-field microscopy

SIGNIFICANCE

Light-field microscopy has achieved success in various applications of life sciences that require high-speed volumetric imaging. However, existing light-field reconstruction algorithms degrade severely in low-light conditions, and the deconvolution process is time-consuming.

AIM

This study aims to develop a noise robustness phase-space deconvolution method with low computational costs.

APPROACH

We reformulate the light-field phase-space deconvolution model into the Fourier domain with random-subset ordering and total-variation (TV) regularization. Additionally, we build a time-division-based multicolor light-field microscopy and conduct the three-dimensional (3D) imaging of the heart beating in zebrafish larva at over 95 Hz with a low light dose.

RESULTS

We demonstrate that this approach reduces computational resources, brings a tenfold speedup, and achieves a tenfold improvement for the noise robustness in terms of SSIM over the state-of-the-art approach.

CONCLUSIONS

We proposed a phase-space deconvolution algorithm for 3D reconstructions in fluorescence imaging. Compared with the state-of-the-art method, we show significant improvement in both computational effectiveness and noise robustness; we further demonstrated practical application on zebrafish larva with low exposure and low light dose.

Shedding light on biology and healthcare-preface to the special issue on Biomedical Optics

This special issue collects 20 excellent papers, spanning NIR II imaging, high-speed imaging, adaptive wavefront shaping, label-free imaging, ultrasensitive detection, polarization optics, photodynamic therapy, and preclinical applications. [Image: see text]