Plane Illumination Research Articles

Decoding interactions between biofilms and DNA nanoparticles.

Decoding interactions between biofilms and DNA nanoparticles.

AI-driven microscopy: from classical analysis to deep learning applications

Abstract Microscopy has revolutionized life sciences by enabling detailed visualization of cellular and subcellular processes. Recent advancements in microscope technology have enhanced our ability to capture complex biological events, generating vast amounts of high-dimensional data. While this opens new avenues for discovery, it also introduces significant challenges in data analysis and interpretation. Modern microscopes can produce terabytes of data in a single experiment, often combining multiple imaging modalities across three or four dimensions. Techniques such as light sheet microscopy (J. Huisken, J. Swoger, F. Del Bene, J. Wittbrodt, and E. H. Stelzer, “Optical sectioning deep inside live embryos by selective plane illumination microscopy,” Science, vol. 305, no. 5686, pp. 1007–1009, 2004), STED (S. W. Hell and J. Wichmann, “Breaking the diffraction resolution limit by stimulated emission: stimulated-emission-depletion fluorescence microscopy,” Opt. Lett., vol. 19, no. 11, pp. 780–782, 1994), STORM (M. J. Rust, M. Bates, and X. Zhuang, “Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM),” Nat. Methods, vol. 3, no. 10, pp. 793–795, 2006), and lattice light sheet microscopy (B.-C. Chen, et al., “Lattice light-sheet microscopy: imaging molecules to embryos at high spatiotemporal resolution,” Science, vol. 346, no. 6208, 2014) have dramatically improved spatial resolution and acquisition speeds. These approaches yield datasets reaching tens of terabytes or more, exposing the limitations of traditional manual and semi-automated analysis methods, which are time-consuming, biased, and struggle with the multidimensional nature of modern microscopy data. To address these challenges, researchers are increasingly adopting artificial intelligence (AI), particularly deep learning models such as convolutional neural networks and transformers (“Deep learning in microscopy,” Nat. Methods, 2019). AI-based tools can automate complex tasks like denoising (A. Krull, T. O. Buchholz, and F. Jug, “Noise2Void – learning denoising from single noisy images,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2019, pp. 2129–2137), segmentation (J. Ma, Y. He, F. Li, L. Han, C. You, and B. Wang, “Segment anything in medical images,” Nat. Commun., vol. 15, p. 654, 2024), and virtual staining (Y. N. Nygate, et al., “Holographic virtual staining of individual biological cells,” Proc. Natl. Acad. Sci. (PNAS), vol. 117, no. 17, 2020), adapting to diverse imaging conditions and enabling scalable analysis of large datasets. This VIEWS article presents the perspective of ZEISS on how AI is transforming microscopy workflows. We highlight practical applications through real-world case studies and discuss how emerging computational tools are accelerating scientific discovery by making sense of complex, high-volume image data.

Evidence for Auditory Stimulus-Specific Adaptation But Not Deviance Detection in Larval Zebrafish Brains.

Animals receive a constant stream of sensory input, and detecting changes in this sensory landscape is critical to their survival. One signature of change detection in humans is the auditory mismatch negativity (MMN), a neural response to unexpected stimuli that deviate from a predictable sequence. This process requires the auditory system to adapt to specific repeated stimuli while remaining sensitive to novel input (stimulus-specific adaptation [SSA]). MMN was originally described in humans, and equivalent responses have been found in other mammals and birds, but it is not known to what extent this deviance detection circuitry is evolutionarily conserved. Here we present the first evidence for SSA in the brain of a teleost fish, using whole-brain calcium imaging of larval zebrafish at single-neuron resolution with selective plane illumination microscopy. We found frequency-specific responses across the brain with variable response amplitudes for frequencies of the same volume and created a loudness curve to model this effect. We presented an auditory "oddball" stimulus in an otherwise predictable train of pure tone stimuli and did not find a population of neurons with specific responses to deviant tones that were not otherwise explained by SSA. Further, we observed no deviance responses to an unexpected omission of a sound in a repetitive sequence of white noise bursts. These findings extend the known scope of auditory adaptation and deviance responses across the evolutionary tree and lay groundwork for future studies to describe the circuitry underlying auditory adaptation at the level of individual neurons.

Combined selective plane illumination microscopy (SPIM) and full-field optical coherence tomography (FF-OCT) for in vivo imaging

Combined selective plane illumination microscopy (SPIM) and full-field optical coherence tomography (FF-OCT) for in vivo imaging

How Tumors Affect Hemodynamics: A Diffusion Study on the Zebrafish Transplantable Model of Medullary Thyroid Carcinoma by Selective Plane Illumination Microscopy.

Medullary thyroid carcinoma (MTC), a rare neuroendocrine tumor comprising 3-5% of thyroid cancers, arises from calcitonin-producing parafollicular C cells. Despite aggressive behavior, surgery remains the primary curative treatment, with limited efficacy reported for radiotherapy and chemotherapy. Recent efforts have explored the pathogenetic mechanisms of MTC, identifying it as a highly vascularized neoplasm overexpressing pro-angiogenic factors. Building on the established benefits of zebrafish embryos, we previously created an in vivo MTC xenograft platform that allows real-time observation of tumor-induced angiogenesis and evaluation of the anti-angiogenic effects of tyrosine kinase inhibitors. In this study, we present a method using selective plane illumination microscopy (SPIM) to characterize vascular permeability in these xenografted embryos. Taking advantage of dextran injections into the blood flow of zebrafish embryos, we found that the diffusion coefficient in embryos grafted with MTC cells was about tenfold lower compared with the same parameter in controls. The results demonstrate the potential of our approach to estimate diffusion parameters, providing valuable insights into vascular permeability changes in MTC-implanted zebrafish embryos compared with controls. Our study sheds light on the intricate vascular biology of MTC, offering a promising tool for future investigations into tumor-induced angiogenesis and therapeutic strategies in diverse neoplasms.

Intelligent Office Lighting Control Using Natural Light and a GA-BP Neural Network-Based System

Intelligent lighting control systems are essential for regulating office illumination. Both illuminance levels and uniformity are important factors influencing the comfort of the office lighting environment. Thus, designing automatic control systems to regulate lighting is essential. This study addresses the issue of natural glare by proposing a method that uses a genetic algorithm (GA) to optimize a backpropagation (BP) neural network model. The model predicts the angle of window slats, with the Sun altitude and azimuth angles as inputs, and the slat angle as the output. For artificial lighting control, a linear function is proposed to manage the relationship between work plane illuminance, natural light intensity, occupancy rates, adjacent luminaire illuminance, and the dimming factor (K). The optimal K value for each luminaire is determined using the least squares method in MATLAB. The intelligent lighting system transmits dimming factors via a ZigBee tree network structure to achieve target illuminance levels. The system’s effectiveness is validated through simulations in DIAlux software, demonstrating that the workplace illuminance in occupied areas reaches 500 lx, while, in unoccupied areas, it reaches 300 lx, with an illuminance uniformity greater than 0.7. This addresses the issue of low illuminance uniformity during daytime. Additionally, the lighting power densities (LPDs) of 1.53 W/m2 and 3.8 W/m2 are well below the specified threshold of 6 W/m2, indicating significant energy savings while maintaining compliance with office lighting standards.

Rapid Whole‐Organ Characterization via Quantitative Light‐Sheet Microscopy

AbstractWhole‐organ imaging and characterization at a submicron level provide abundant information on development and diseases while remaining a big challenge, especially in the context of time load. Herein, a quantitative light‐sheet microscopy platform that enabled highly time‐efficient assessments of fibrous structures within the intact cleared tissue is developed. Dual‐view inverted selective plane illumination microscopy (diSPIM), followed by improved registration and deconvolution, led to submicron isotropic imaging of mouse upper genital tract with one hundred‐fold speed‐ups than previous efforts. Further, optical metrics quantifying 3D local density and structural complexity of targets based on parallel and vectorized convolution in both spatial and frequency domains are developed. Collectively, ≈400–2000 fold increases in time efficiency counting for imaging, postprocessing, and quantitative characterization compared to the traditional method is gained. Using this platform, automatic identification of medulla and cortex within the mouse ovary at over 90% overlap with manual selection by anatomy experts is achieved. Additionally, heterogeneous distributions of immune cells in the mouse ovary and fallopian tube, offering a unique perspective for understanding the immune microenvironment are discovered. This work paves the way for future whole‐organ study, and exhibits potential with promise for offering mechanistic insights into physiological and pathological alterations of biological tissues.

Testing the use of daylight-linked control systems to address integrative lighting and energy savings in office buildings

Testing the use of daylight-linked control systems to address integrative lighting and energy savings in office buildings

LiveLattice: Real-time visualisation of tilted light-sheet microscopy data using a memory-efficient transformation algorithm.

Light-sheet fluorescence microscopy (LSFM), a prominent fluorescence microscopy technique, offers enhanced temporal resolution for imaging biological samples in four dimensions (4D; x, y, z, time). Some of the most recent implementations, including inverted selective plane illumination microscopy (iSPIM) and lattice light-sheet microscopy (LLSM), move the sample substrate at an oblique angle relative to the detection objective's optical axis. Data from such tilted-sample-scan LSFMs require subsequent deskewing and rotation for proper visualisation and analysis. Such data preprocessing operations currently demand substantial memory allocation and pose significant computational challenges for large 4D dataset. The consequence is prolonged data preprocessing time compared to data acquisition time, which limits the ability for live-viewing the data as it is being captured by the microscope. To enable the fast preprocessing of large light-sheet microscopy datasets without significant hardware demand, we have developed WH-Transform, a memory-efficient transformation algorithm for deskewing and rotating the raw dataset, significantly reducing memory usage and the run time by more than 10-fold for large image stacks. Benchmarked against the conventional method and existing software, our approach demonstrates linear runtime compared to the cubic and quadratic runtime of the other approaches. Preprocessing a raw 3D volume of 2 GB (512 × 1536 × 600 pixels) can be accomplished in 3 s using a GPU with 24 GB of memory on a single workstation. Applied to 4D LLSM datasets of human hepatocytes, lung organoid tissue and brain organoid tissue, our method provided rapid and accurate preprocessing within seconds. Importantly, such preprocessing speeds now allow visualisation of the raw microscope data stream in real time, significantly improving the usability of LLSM in biology. In summary, this advancement holds transformative potential for light-sheet microscopy, enabling real-time, on-the-fly data preprocessing, visualisation, and analysis on standard workstations, thereby revolutionising biological imaging applications for LLSM and similar microscopes.

Affordable ultra-widefield smartphone PedCam for comprehensive pediatric retinal examination.

Widefield fundus photography is critical for the detection, documentation, and management of pediatric eye diseases. Existing clinical pediatric fundus cameras offer a limited field of view (FOV) and suboptimal image contrast, hindering comprehensive peripheral retina examination. Additionally, the high cost and lack of portability of commercial devices restrict their use in resource-limited settings. We introduce a cost-effective smartphone-based pediatric camera (PedCam) that provides a 180° eye angle (126° visual angle) snapshot FOV. Utilizing trans-pars planar illumination, the device enables nonmydriatic imaging by allocating the pupil exclusively for imaging, eliminating the need for pharmacological pupillary dilation. By adjusting the optical axis of the PedCam relative to the ocular axis, the effective FOV can be expanded up to 240° eye angle (180° visual angle), enabling complete retinal evaluation. This innovative smartphone PedCam represents a significant advancement in affordable telemedicine for the screening, monitoring, and management of retinopathy of prematurity and other pediatric eye conditions.

Model based optimization for refractive index mismatched light sheet imaging.

Selective plane illumination microscopy (SPIM) is an optical sectioning imaging approach based on orthogonal light pathways for excitation and detection. The excitation pathway has an inverse relation between the optical sectioning strength and the effective field of view (FOV). Multiple approaches exist to extend the effective FOV, and here we focus on remote focusing to axially scan the light sheet, synchronized with a CMOS camera's rolling shutter. A typical axially scanned SPIM configuration for imaging large samples utilizes a tunable optic for remote focusing, paired with air objectives focused into higher refractive index media. To quantitatively explore the effect of remote focus choices and sample space refractive index mismatch on light sheet intensity distributions, we developed an open-source computational approach for integrating ray tracing and field propagation. We validate our model's performance against experimental light sheet profiles for various SPIM configurations. Our findings indicate that optimizing the position of the sample chamber relative to the excitation optics can enhance image quality by balancing aberrations induced by refractive index mismatch. We validate this prediction using a home-built, large sample axially scanned SPIM configuration and calibration samples. Our open-source, extensible modeling software can easily extend to explore optimal imaging configurations in diverse light sheet imaging settings.

Expansion-assisted selective plane illumination microscopy for nanoscale imaging of centimeter-scale tissues.

Recent advances in tissue processing, labeling, and fluorescence microscopy are providing unprecedented views of the structure of cells and tissues at sub-diffraction resolutions and near single molecule sensitivity, driving discoveries in diverse fields of biology, including neuroscience. Biological tissue is organized over scales of nanometers to centimeters. Harnessing molecular imaging across intact, three-dimensional samples on this scale requires new types of microscopes with larger fields of view and working distance, as well as higher throughput. We present a new expansion-assisted selective plane illumination microscope (ExA-SPIM) with aberration-free 1×1×3 μm optical resolution over a large field of view (10.6×8.0 mm 2 ) and working distance (35 mm) at speeds up to 946 megavoxels/sec. Combined with new tissue clearing and expansion methods, the microscope allows imaging centimeter-scale samples with 250×250×750 nm optical resolution (4× expansion), including entire mouse brains, with high contrast and without sectioning. We illustrate ExA-SPIM by reconstructing individual neurons across the mouse brain, imaging cortico-spinal neurons in the macaque motor cortex, and visualizing axons in human white matter.

EVIDENCE FOR AUDITORY STIMULUS-SPECIFIC ADAPTATION BUT NOT DEVIANCE DETECTION IN LARVAL ZEBRAFISH BRAINS.

Animals receive a constant stream of sensory input, and detecting changes in this sensory landscape is critical to their survival. One signature of change detection in humans is the auditory mismatch negativity (MMN), a neural response to unexpected stimuli that deviate from a predictable sequence. This process requires the auditory system to adapt to specific repeated stimuli while remaining sensitive to novel input (stimulus-specific adaptation). MMN was originally described in humans, and equivalent responses have been found in other mammals and birds, but it is not known to what extent this deviance detection circuitry is evolutionarily conserved. Here we present the first evidence for stimulus-specific adaptation in the brain of a teleost fish, using whole-brain calcium imaging of larval zebrafish at single-neuron resolution with selective plane illumination microscopy. We found frequency-specific responses across the brain with variable response amplitudes for frequencies of the same volume, and created a loudness curve to model this effect. We presented an auditory 'oddball' stimulus in an otherwise predictable train of pure tone stimuli, and did not find a population of neurons with specific responses to deviant tones that were not otherwise explained by stimulus-specific adaptation. Further, we observed no deviance responses to an unexpected omission of a sound in a repetitive sequence of white noise bursts. These findings extend the known scope of auditory adaptation and deviance responses across the evolutionary tree, and lay groundwork for future studies to describe the circuitry underlying auditory adaptation at the level of individual neurons.

Comparison of polystyrene and hydrogel microcarriers for optical imaging of adherent cells.

The ability to observe and monitor cell density and morphology has been imperative for assessing the health of a cell culture and for producing high quality, high yield cell cultures for decades. Microcarrier-based cultures, used for large-scale cellular expansion processes, are not compatible with traditional visualization-based methods, such as widefield microscopy, due to their thickness and material composition. Here, we assess the optical imaging compatibilities of commercial polystyrene microcarriers versus custom-fabricated gelatin methacryloyl (gelMA) microcarriers for non-destructive and non-invasive visualization of the entire microcarrier surface, direct cell enumeration, and sub-cellular visualization of mesenchymal stem/stromal cells. Mie scattering and wavefront error simulations of the polystyrene and gelMA microcarriers were performed to assess the potential for elastic scattering-based imaging of adherent cells. A Zeiss Z.1 light-sheet microscope was adapted to perform light-sheet tomography using label-free elastic scattering contrast from planar side illumination to achieve optical sectioning and permit non-invasive and non-destructive, in toto, three-dimensional, high-resolution visualization of cells cultured on microcarriers. The polystyrene microcarrier prevents visualization of cells on the distal half of the microcarrier using either fluorescence or elastic scattering contrast, whereas the gelMA microcarrier allows for high fidelity visualization of cell morphology and quantification of cell density using light-sheet fluorescence microscopy and tomography. The combination of optical-quality gelMA microcarriers and label-free light-sheet tomography will facilitate enhanced control of bioreactor-microcarrier cell culture processes.

Multispectral imaging for characterizing autofluorescent tissues

Selective Plane Illumination Microscopy (SPIM) has become an emerging technology since its first application for 3D in-vivo imaging of the development of a living organism. An extensive number of works have been published, improving both the speed of acquisition and the resolution of the systems. Furthermore, multispectral imaging allows the effective separation of overlapping signals associated with different fluorophores from the spectrum over the whole field-of-view of the analyzed sample. To eliminate the need of using fluorescent dyes, this technique can also be applied to autofluorescence imaging. However, the effective separation of the overlapped spectra in autofluorescence imaging necessitates the use of mathematical tools. In this work, we explore the application of a method based on Principal Component Analysis (PCA) that enables tissue characterization upon spectral autofluorescence data without the use of fluorophores. Thus, enabling the separation of different tissue types in fixed and living samples with no need of staining techniques. Two procedures are described for acquiring spectral data, including a single excitation based method and a multi-excitation scanning approach. In both cases, we demonstrate the effective separation of various tissue types based on their unique autofluorescence spectra.

Simulation-based analysis of window paper effects on daylighting of traditional Beijing siheyuan

Paper is a widely used light-transmissive material in Chinese traditional buildings. To establish and simulation methods for window paper and study the temporal and spatial features of daylighting in Beijing siheyuan, we conducted model measurements and simulations based on dynamic meteorological parameters in the main and side houses. It has been found that in comparison with glass, window paper has following features in terms of daylighting: (1) It improves the uniformity of illuminance in a room and reduces seasonal differences in illuminance; (2) It can improve ground illuminance and the illuminance at the rear wall, and reduce work plane illuminance near the window; (3) It reduces interior illuminance in general and increases the chance of glare in the main house at noon in winter. This study clarified the lighting significance of window paper and provided a reference for the application of diffuse transmissive materials with window paper-like effects.

A time-correlated single photon counting SPAD array camera with a bespoke data-processing algorithm for lightsheet fluorescence lifetime imaging (FLIM) and FLIM videos

A wide-field microscope with epi-fluorescence and selective plane illumination was combined with a single-photon avalanche diode (SPAD) array camera to enable live-cell fluorescence lifetime imaging (FLIM) using time-correlated single-photon counting (TCSPC). The camera sensor comprised of 192×128\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext {192}\ imes \ ext {128}$$\\end{document} pixels, each integrating a single SPAD and a time-to-digital converter. Jointly, they produced a stream of single-photon images of photon arrival times with ≈38 ps\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx \ ext {38 ps}$$\\end{document} accuracy. The photon arrival times were subject to systematic delays and nonlinearities, which were corrected by a Monte-Carlo algorithm. The SPAD camera was then applied to FLIM where histogramming the resulting photon arrival times in each pixel resulted in decays compatible with common data processing pipelines for fluorescence lifetime analysis. The capabilities of the TCSPC camera-based FLIM microscope were demonstrated by imaging living unicellular photosynthetic algae and artificial lipid vesicles. Epi-fluorescence illumination enabled rapid fluorescence lifetime imaging of living cells and selective-plane illumination enabled 3-dimensional FLIM of stationary samples.

A laser field synchronous scanning imaging system for underwater long-range detection

A laser field synchronous scanning imaging system for underwater long-range detection

Daylight Comfort Performance of a Vertical Fin Shading System: Annual Simulation and Experimental Testing of a Prototype

This study aims to develop and evaluate a vertically rotated fin shading system for an energy-efficient, user-friendly office space. The system was designed to protect a 4 × 8 m office room with a south-facing facade from excessive solar radiation and glare. The shading system was modelled and simulated using Rhino/Ladybug 1.6.0 software with Radiance engine, based on real-weather data (*.epw file) for Wrocław, Poland at 51° lat. The simulation calculated the useful daylight illuminance (UDI) for 300–3000 lux and the daylight glare probability (DGP) for ten static and four kinetic variants of the system. The optimal angle of the fin rotation for the static variant was found to be α = 40°. The kinetic variants were activated when the work plane illuminance exceeded 3000 lux, as detected by an internal sensor “A”. The simulation results show that the kinetic system improved the daylight uniformity in the office room, achieving UDI300–3000 values above 80% for more than 40% of the room area. A prototype of the system in a 1:20 scale was built and tested on a testbed at Wrocław University of Science and Technology, using TESTO THL 160 data loggers. The measurements were conducted for a week in early November 2023, and three clear days were selected for analysis. The measurement results indicate that the low solar altitude on clear days causes high illuminance peaks (15–18 Klux) and significant contrast in the room, leading to unsatisfactory DGP values consistent with the simulation outcomes. Therefore, the study concludes that the proposed system may need an additional shading device to prevent glare during periods of low solar altitudes.

Motion-resistant three-wavelength spatial frequency domain imaging system with ambient light suppression using an 8-tap CMOS image sensor.

We present a motion-resistant three-wavelength spatial frequency domain imaging (SFDI) system with ambient light suppression using an 8-tap complementary metal-oxide semiconductor (CMOS) image sensor (CIS) developed at Shizuoka University. The system addresses limitations in conventional SFDI systems, enabling reliable measurements in challenging imaging scenarios that are closer to real-world conditions. Our study demonstrates a three-wavelength SFDI system based on an 8-tap CIS. We demonstrate and evaluate the system's capability of mitigating motion artifacts and ambient light bias through tissue phantom reflectance experiments and in vivo volar forearm experiments. We incorporated the Hilbert transform to reduce the required number of projected patterns per wavelength from three to two per spatial frequency. The 8-tap image sensor has eight charge storage diodes per pixel; therefore, simultaneous image acquisition of eight images based on multi-exposure is possible. Taking advantage of this feature, the sensor simultaneously acquires images for planar illumination, sinusoidal pattern projection at three wavelengths, and ambient light. The ambient light bias is eliminated by subtracting the ambient light image from the others. Motion artifacts are suppressed by reducing the exposure and projection time for each pattern while maintaining sufficient signal levels by repeating the exposure. The system is compared to a conventional SFDI system in tissue phantom experiments and then in vivo measurements of human volar forearms. The 8-tap image sensor-based SFDI system achieved an acquisition rate of 9.4 frame sets per second, with three repeated exposures during each accumulation period. The diffuse reflectance maps of three different tissue phantoms using the conventional SFDI system and the 8-tap image sensor-based SFDI system showed good agreement except for high scattering phantoms. For the in vivo volar forearm measurements, our system successfully measured total hemoglobin concentration, tissue oxygen saturation, and reduced scattering coefficient maps of the subject during motion (16.5cm/s) and under ambient light (28.9lx), exhibiting fewer motion artifacts compared with the conventional SFDI. We demonstrated the potential for motion-resistant three-wavelength SFDI system with ambient light suppression using an 8-tap CIS.