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The conceptual foundation of light-sheet microscopy dates back to 1902 when Siedentopf and Zsigmondy developed a microscope, which they termed the “ultramicroscope”, to study the scattering of visible light from sub-wavelength colloidal particles. The low energy load in light-sheet microscopy experiments enables optimal utilization of the photon budget and affords whole-animal imaging with high spatial resolution and high temporal resolution at the same time. First-generation laser light-sheet fluorescence microscopes acquired volumetric data by translating the sample sequentially across the stationary light-sheet and detection focal plane. A majority of functional imaging with light-sheet microscopy in the mammalian brain has thus far been performed on ex vivo tissues. Whole-brain functional imaging experiments stand out among other types of light-sheet microscopy experiments in particular with respect to their unique performance requirements. The primary speed bottleneck in state-of-the-art light-sheet microscopes is camera performance.

© 2020, Springer Nature Limited. State-of-the-art tissue-clearing methods provide subcellular-level optical access to intact tissues from individual organs and even to some entire mammals. When combined with light-sheet microscopy and automated approaches to image analysis, existing tissue-clearing methods can speed up and may reduce the cost of conventional histology by several orders of magnitude. In addition, tissue-clearing chemistry allows whole-organ antibody labelling, which can be applied even to thick human tissues. By combining the most powerful labelling, clearing, imaging and data-analysis tools, scientists are extracting structural and functional cellular and subcellular information on complex mammalian bodies and large human specimens at an accelerated pace. The rapid generation of terabyte-scale imaging data furthermore creates a high demand for efficient computational approaches that tackle challenges in large-scale data analysis and management. In this Review, we discuss how tissue-clearing methods could provide an unbiased, system-level view of mammalian bodies and human specimens and discuss future opportunities for the use of these methods in human neuroscience.

We describe the implementation and use of an adaptive imaging framework for optimizing spatial resolution and signal strength in a light-sheet microscope. The framework, termed AutoPilot, comprises hardware and software modules for automatically measuring and compensating for mismatches between light-sheet and detection focal planes in living specimens. Our protocol enables researchers to introduce adaptive imaging capabilities in an existing light-sheet microscope or use our SiMView microscope blueprint to set up a new adaptive multiview light-sheet microscope. The protocol describes (i) the mechano-optical implementation of the adaptive imaging hardware, including technical drawings for all custom microscope components; (ii) the algorithms and software library for automated adaptive imaging, including the pseudocode and annotated source code for all software modules; and (iii) the execution of adaptive imaging experiments, as well as the configuration and practical use of the AutoPilot framework. Setup of the adaptive imaging hardware and software takes 1–2 weeks each. Previous experience with light-sheet microscopy and some familiarity with software engineering and building of optical instruments are recommended. Successful implementation of the protocol recovers near diffraction-limited performance in many parts of typical multicellular organisms studied with light-sheet microscopy, such as fruit fly and zebrafish embryos, for which resolution and signal strength are improved two- to fivefold. This protocol describes how to implement and apply an adaptive light-sheet microscopy framework (AutoPilot). The procedure can be used to introduce AutoPilot in an existing microscope or to set up a new adaptive multiview light-sheet microscope.

Tissue clearing and light-sheet microscopy have over a 100-year-long history, yet only recently have these fields been combined to facilitate novel experiments and measurements in neuroscience. Since tissue-clearing methods were first combined with modernized light-sheet microscopy a decade ago, the performance of both technologies have rapidly improved, broadening their applications. Here we review the state-of-the-art of tissue clearing methods and light-sheet microscopy and discuss applications of these techniques in profiling cells and circuits in mice. We examine outstanding challenges and future opportunities for expanding these techniques to achieve brain-wide profiling of cells and circuits in primates and humans. Such integration will help provide a systems level understanding of physiology and pathology of our central nervous system.

Animal development is a complex and dynamic process orchestrated by exquisitely timed cell lineage commitment, divisions, migration, and morphological changes at the single-cell level. In the past decade, extensive genetic, stem cell, and genomic studies provided crucial insights into molecular underpinnings and the functional importance of genetic pathways governing various cellular differentiation processes. However, it is still largely unknown how the precise coordination of these pathways is achieved at the whole-organism level and how the highly regulated spatiotemporal choreography of development is established in turn. Here, we discuss the latest technological advances in imaging and single-cell genomics that hold great promise for advancing our understanding of this intricate process. We propose an integrated approach that combines such methods to quantitatively decipher in vivo cellular dynamic behaviors and their underlying molecular mechanisms at the systems level with single-cell, single-molecule resolution.

Light-sheet imaging of cleared and expanded samples creates terabyte-sized datasets that consist of many unaligned three-dimensional image tiles, which must be reconstructed before analysis. We developed the BigStitcher software to address this challenge. BigStitcher enables interactive visualization, fast and precise alignment, spatially resolved quality estimation, real-time fusion and deconvolution of dual-illumination, multitile, multiview datasets. The software also compensates for optical effects, thereby improving accuracy and enabling subsequent biological analysis.

Light-sheet microscopy is a powerful method for imaging the development and function of complex biological systems at high spatiotemporal resolution and over long time scales. Such experiments typically generate terabytes of multidimensional image data, and thus they demand efficient computational solutions for data management, processing and analysis. We present protocols and software to tackle these steps, focusing on the imaging-based study of animal development. Our protocols facilitate (i) high-speed lossless data compression and content-based multiview image fusion optimized for multicore CPU architectures, reducing image data size 30-500-fold; (ii) automated large-scale cell tracking and segmentation; and (iii) visualization, editing and annotation of multiterabyte image data and cell-lineage reconstructions with tens of millions of data points. These software modules are open source. They provide high data throughput using a single computer workstation and are readily applicable to a wide spectrum of biological model systems.

In vivo imaging applications typically require carefully balancing conflicting parameters. Often it is necessary to achieve high imaging speed, low photo-bleaching, and photo-toxicity, good three-dimensional resolution, high signal-to-noise ratio, and excellent physical coverage at the same time. Light-sheet microscopy provides good performance in all of these categories, and is thus emerging as a particularly powerful live imaging method for the life sciences. We see an outstanding potential for applying light-sheet microscopy to the study of development and function of the early nervous system in vertebrates and higher invertebrates. Here, we review state-of-the-art approaches to live imaging of early development, and show how the unique capabilities of light-sheet microscopy can further advance our understanding of the development and function of the nervous system. We discuss key considerations in the design of light-sheet microscopy experiments, including sample preparation and fluorescent marker strategies, and provide an outlook for future directions in the field.

Motivation: Optical flow is a key method used for quantitative motion estimation of biological structures in light microscopy. It has also been used as a key module in segmentation and tracking systems and is considered a mature technology in the field of computer vision. However, most of the research focused on 2D natural images, which are small in size and rich in edges and texture information. In contrast, 3D time-lapse recordings of biological specimens comprise up to several terabytes of image data and often exhibit complex object dynamics as well as blurring due to the point-spread-function of the microscope. Thus, new approaches to optical flow are required to improve performance for such data. Results: We solve optical flow in large 3D time-lapse microscopy datasets by defining a Markov random field (MRF) over super-voxels in the foreground and applying motion smoothness constraints between super-voxels instead of voxel-wise. This model is tailored to the specific characteristics of light microscopy datasets: super-voxels help registration in textureless areas, the MRF over super-voxels efficiently propagates motion information between neighboring cells and the background subtraction and super-voxels reduce the dimensionality of the problem by an order of magnitude. We validate our approach on large 3D time-lapse datasets of Drosophila and zebrafish development by analyzing cell motion patterns. We show that our approach is, on average, 10 × faster than commonly used optical flow implementations in the Insight Tool-Kit (ITK) and reduces the average flow end point error by 50% in regions with complex dynamic processes, such as cell divisions. Availability: Source code freely available in the Software section at http://janelia.org/lab/keller-lab. Contact: amatf@janelia.hhmi.org or kellerp@janelia.hhmi.org Supplementary information: Supplementary data are available at Bioinformatics online.

Optimal image quality in light-sheet microscopy requires a perfect overlap between the illuminating light sheet and the focal plane of the detection objective. However, mismatches between the light-sheet and detection planes are common owing to the spatiotemporally varying optical properties of living specimens. Here we present the AutoPilot framework, an automated method for spatiotemporally adaptive imaging that integrates (i) a multi-view light-sheet microscope capable of digitally translating and rotating light-sheet and detection planes in three dimensions and (ii) a computational method that continuously optimizes spatial resolution across the specimen volume in real time. We demonstrate long-term adaptive imaging of entire developing zebrafish (Danio rerio) and Drosophila melanogaster embryos and perform adaptive whole-brain functional imaging in larval zebrafish. Our method improves spatial resolution and signal strength two to five-fold, recovers cellular and sub-cellular structures in many regions that are not resolved by non-adaptive imaging, adapts to spatiotemporal dynamics of genetically encoded fluorescent markers and robustly optimizes imaging performance during large-scale morphogenetic changes in living organisms.

We developed isotropic multiview (IsoView) light-sheet microscopy in order to image fast cellular dynamics, such as cell movements in an entire developing embryo or neuronal activity throughput an entire brain or nervous system, with high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To achieve high temporal resolution and high spatial resolution at the same time, IsoView microscopy rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. In a post-processing step, these four views are then combined by means of high-throughput multiview deconvolution to yield images with a system resolution of ≤ 450 nm in all three dimensions. Using IsoView microscopy, we performed whole-animal functional imaging of Drosophila embryos and larvae at a spatial resolution of 1.1-2.5 μm and at a temporal resolution of 2 Hz for up to 9 hours. We also performed whole-brain functional imaging in larval zebrafish and multicolor imaging of fast cellular dynamics across entire, gastrulating Drosophila embryos with isotropic, sub-cellular resolution. Compared with conventional (spatially anisotropic) light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, such as lattice lightsheet microscopy or diSPIM, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

Simultaneous multiview light-sheet microscopy using two illumination and two detection arms with one- or two-photon illumination is coupled to a fast data acquisition framework and analysis pipeline for quantitative imaging and tracking of individual cells and the developing nervous system throughout a living fly embryo. A related paper by Krzic et al. is also in this issue.

The observation of biological processes in their natural in vivo context is a key requirement for quantitative experimental studies in the life sciences. In many instances, it will be crucial to achieve high temporal and spatial resolution over long periods of time without compromising the physiological development of the specimen. Here, we discuss the principles underlying light sheet-based fluorescence microscopes. The most recent implementation DSLM is a tool optimized to deliver quantitative data for entire embryos at high spatio-temporal resolution. We compare DSLM to the two established light microscopy techniques: confocal and two-photon fluorescence microscopy. DSLM provides up to 50 times higher imaging speeds and a 10-100 times higher signal-to-noise ratio, while exposing the specimens to at least three orders of magnitude less light energy than confocal and two-photon fluorescence microscopes. We conclude with a perspective for future development.

Understanding how the brain works in tight concert with the rest of the central nervous system (CNS) hinges upon knowledge of coordinated activity patterns across the whole CNS. We present a method for measuring activity in an entire, non-transparent CNS with high spatiotemporal resolution. We combine a light-sheet microscope capable of simultaneous multi-view imaging at volumetric speeds 25-fold faster than the state-of-the-art, a whole-CNS imaging assay for the isolated Drosophila larval CNS and a computational framework for analysing multi-view, whole-CNS calcium imaging data. We image both brain and ventral nerve cord, covering the entire CNS at 2 or 5 Hz with two- or one-photon excitation, respectively. By mapping network activity during fictive behaviours and quantitatively comparing high-resolution whole-CNS activity maps across individuals, we predict functional connections between CNS regions and reveal neurons in the brain that identify type and temporal state of motor programs executed in the ventral nerve cord., To understand how neuronal networks function, it is important to measure neuronal network activity at the systems level. Here Lemon et al. develop a framework that combines a high-speed multi-view light-sheet microscope, a whole-CNS imaging assay and computational tools to demonstrate simultaneous functional imaging across the entire isolated Drosophila larval CNS.

Imaging fast cellular dynamics across large specimens requires high resolution in all dimensions, high imaging speeds, good physical coverage and low photo-damage. To meet these requirements, we developed isotropic multiview (IsoView) light-sheet microscopy, which rapidly images large specimens via simultaneous light-sheet illumination and fluorescence detection along four orthogonal directions. Combining these four views by means of high-throughput multiview deconvolution yields images with high resolution in all three dimensions. We demonstrate whole-animal functional imaging of Drosophila larvae at a spatial resolution of 1.1-2.5 μm and temporal resolution of 2 Hz for several hours. We also present spatially isotropic whole-brain functional imaging in Danio rerio larvae and spatially isotropic multicolor imaging of fast cellular dynamics across gastrulating Drosophila embryos. Compared with conventional light-sheet microscopy, IsoView microscopy improves spatial resolution at least sevenfold and decreases resolution anisotropy at least threefold. Compared with existing high-resolution light-sheet techniques, IsoView microscopy effectively doubles the penetration depth and provides subsecond temporal resolution for specimens 400-fold larger than could previously be imaged.

The fruit fly is an excellent model system for investigating the sequence of epithelial tissue invaginations constituting the process of gastrulation. By combining recent advancements in light sheet fluorescence microscopy (LSFM) and image processing, the three-dimensional fly embryo morphology and relevant gene expression patterns can be accurately recorded throughout the entire process of embryogenesis. LSFM provides exceptionally high imaging speed, high signal-to-noise ratio, low level of photoinduced damage, and good optical penetration depth. This powerful combination of capabilities makes LSFM particularly suitable for live imaging of the fly embryo.The resulting high-information-content image data are subsequently processed to obtain the outlines of cells and cell nuclei, as well as the geometry of the whole embryo tissue by image segmentation. Furthermore, morphodynamics information is extracted by computationally tracking objects in the image. Towards that goal we describe the successful implementation of a fast fitting strategy of Gaussian mixture models.The data obtained by image processing is well-suited for hypothesis testing of the detailed biomechanics of the gastrulating embryo. Typically this involves constructing computational mechanics models that consist of an objective function providing an estimate of strain energy for a given morphological configuration of the tissue, and a numerical minimization mechanism of this energy, achieved by varying morphological parameters.In this chapter, we provide an overview of in vivo imaging of fruit fly embryos using LSFM, computational tools suitable for processing the resulting images, and examples of computational biomechanical simulations of fly embryo gastrulation.

This protocol describes how to observe gastrulation in living mouse embryos by using light-sheet microscopy and computational tools to analyze the resulting image data at the single-cell level. We describe a series of techniques needed to image the embryos under physiological conditions, including how to hold mouse embryos without agarose embedding, how to transfer embryos without air exposure and how to construct environmental chambers for live imaging by digital scanned light-sheet microscopy (DSLM). Computational tools include manual and semiautomatic tracking programs that are developed for analyzing the large 4D data sets acquired with this system. Note that this protocol does not include details of how to build the light-sheet microscope itself. Time-lapse imaging ends within 12 h, with subsequent tracking analysis requiring 3-6 d. Other than some mouse-handling skills, this protocol requires no advanced skills or knowledge. Light-sheet microscopes are becoming more widely available, and thus the techniques outlined in this paper should be helpful for investigating mouse embryogenesis.

Morphogenesis, the development of the shape of an organism, is a dynamic process on a multitude of scales, from fast subcellular rearrangements and cell movements to slow structural changes at the whole-organism level. Live-imaging approaches based on light microscopy reveal the intricate dynamics of this process and are thus indispensable for investigating the underlying mechanisms. This Review discusses emerging imaging techniques that can record morphogenesis at temporal scales from seconds to days and at spatial scales from hundreds of nanometers to several millimeters. To unlock their full potential, these methods need to be matched with new computational approaches and physical models that help convert highly complex image data sets into biological insights.

The zebrafish Danio rerio has emerged as a powerful vertebrate model system that lends itself particularly well to quantitative investigations with live imaging approaches, owing to its exceptionally high optical clarity in embryonic and larval stages. Recent advances in light microscopy technology enable comprehensive analyses of cellular dynamics during zebrafish embryonic development, systematic mapping of gene expression dynamics, quantitative reconstruction of mutant phenotypes and the system-level biophysical study of morphogenesis. Despite these technical breakthroughs, it remains challenging to design and implement experiments for in vivo long-term imaging at high spatio-temporal resolution. This article discusses the fundamental challenges in zebrafish long-term live imaging, provides experimental protocols and highlights key properties and capabilities of advanced fluorescence microscopes. The article focuses in particular on experimental assays based on light sheet-based fluorescence microscopy, an emerging imaging technology that achieves exceptionally high imaging speeds and excellent signal-to-noise ratios, while minimizing light-induced damage to the specimen. This unique combination of capabilities makes light sheet microscopy an indispensable tool for the in vivo long-term imaging of large developing organisms.

Light sheet-based fluorescence microscopy (LSFM) is emerging as a powerful imaging technique for the life sciences. LSFM provides an exceptionally high imaging speed, high signal-to-noise ratio, low level of photo-bleaching, and good optical penetration depth. This unique combination of capabilities makes light sheet-based microscopes highly suitable for live imaging applications. Here, we provide an overview of light sheet-based microscopy assays for in vitro and in vivo imaging of biological samples, including cell extracts, soft gels, and large multicellular organisms. We furthermore describe computational tools for basic image processing and data inspection.

Embryonic development is one of the most complex processes encountered in biology. In vertebrates and higher invertebrates, a single cell transforms into a fully functional organism comprising several tens of thousands of cells, arranged in tissues and organs that perform impressive tasks. In vivo observation of this biological process at high spatiotemporal resolution and over long periods of time is crucial for quantitative developmental biology. Importantly, such recordings must be realized without compromising the physiological development of the specimen. In digital scanned laser light-sheet fluorescence microscopy (DSLM), a specimen is rapidly scanned with a thin sheet of light while fluorescence is recorded perpendicular to the axis of illumination with a camera. Combining light-sheet technology and fast laser scanning, DSLM delivers quantitative data for entire embryos at high spatiotemporal resolution. Compared with confocal and two-photon fluorescence microscopy, DSLM exposes the embryo to at least three orders of magnitude less light energy, but still provides up to 50 times faster imaging speeds and a 10–100-fold higher signal-to-noise ratio. By using automated image processing algorithms, DSLM images of embryogenesis can be converted into a digital representation. These digital embryos permit following cells as a function of time, revealing cell fate as well as cell origin. By means of such analyses, developmental building plans of tissues and organs can be determined in a whole-embryo context. This article presents a sample preparation and imaging protocol for studying the development of whole zebrafish and Drosophila embryos using DSLM.

Light sheet microscopy is a versatile imaging technique with a unique combination of capabilities. It provides high imaging speed, high signal-to-noise ratio and low levels of photobleaching and phototoxic effects. These properties are crucial in a wide range of applications in the life sciences, from live imaging of fast dynamic processes in single cells to long-term observation of developmental dynamics in entire large organisms. When combined with tissue clearing methods, light sheet microscopy furthermore allows rapid imaging of large specimens with excellent coverage and high spatial resolution. Even samples up to the size of entire mammalian brains can be efficiently recorded and quantitatively analyzed. Here, we provide an overview of the history of light sheet microscopy, review the development of tissue clearing methods, and discuss recent technical breakthroughs that have the potential to influence the future direction of the field.

We present an experimental investigation of microtubule dynamic instability in three dimensions, based on laser light-sheet fluorescence microscopy. We introduce three-dimensional (3D) preparation of Xenopus laevis egg extracts in Teflon-based cylinders and provide algorithms for 3D image processing. Our approach gives experimental access to the intrinsic dynamic properties of microtubules and to microtubule population statistics in single asters. We obtain evidence for a stochastic nature of microtubule pausing.

Visualization of cellular and molecular processes is an indispensable tool for cell biologists, and innovations in microscopy methods unfailingly lead to new biological discoveries. Today, light microscopy (LM) provides ever-higher spatial and temporal resolution and visualization of biological process over enormous ranges. Electron microscopy (EM) is moving into the atomic resolution regime and allowing cellular analyses that are more physiological and sophisticated in scope. Importantly, much is being gained by combining multiple approaches, (e.g., LM and EM) to take advantage of their complementary strengths. The advent of high-throughput microscopies has led to a common need for sophisticated computational methods to quantitatively analyze huge amounts of data and translate images into new biological insights. In vivo imaging requires carefully balancing conflicting parameters to achieve high imaging speed, low photobleaching and phototoxicity, good three-dimensional resolution, high signal-to-noise ratio, and excellent physical coverage. Light-sheet microscopy provides outstanding performance in all of these categories and has become a key imaging method for the life sciences. Philipp Keller (Janelia Farm) showed how entire Drosophila embryos can be imaged throughout embryogenesis at a spatiotemporal resolution that enables comprehensive cell tracking. The use of automated approaches for computational image analysis enables systematical reconstruction of cell lineage information from such recordings in real time. Progress in the light-sheet microscopy field is faster than ever, and further improvements in temporal and spatial resolution are expected in the near future. These capabilities will directly synergize with the rapid progress in related fields, such as the development of advanced fluorescent reporter strategies, powerful approaches to high-throughput data analysis, and computational tools for biophysical modeling, opening up exciting new opportunities for microscopy-based research in the life sciences. Superresolution imaging is enabling the visualization of intracellular relationships unobtainable using traditional fluorescent microscopy. However, different superresolution techniques are based on distinct physical principles to break conventional light microscopy limitations, and these principles determine the apparent size of the biological structure being imaged. The 25-nm-microtubule diameter appears to be between 30 and 120 nm, depending on the technique used. These specific principles also define the acquisition speed of each method, resulting in a family of techniques, with each technique optimized for both size (e.g., organelles vs. transmembrane receptors) and dynamics (e.g., slow transport vs. diffusion). Recent advances that combine multiple approaches to address a biological question show great promise for overcoming these limitations. Catherine Galbraith (National Institutes of Health) showed how live-cell superresolution imaging of single molecules can be combined with computer-vision tracking and conventional microscopy. This integration provides a dense functional dynamics map that can be used to correlate the behavior of multiple proteins to that of the entire cell, while visualizing biochemistry at the single-molecule level. Because biology is the complex integration of multiple systems, the combination of multiple imaging approaches presents the greatest opportunity for making meaningful discoveries. Cellular transmission EM has traditionally suffered from the need to section the sample. Sectioning of resin-embedded material is relatively easy but can suffer from poor sample preservation, while cryosectioning of frozen-hydrated samples is inefficient and hampered by cutting and compression artifacts. A recent breakthrough is the use of focus ion beam (FIB) methodology to carve out cellular slices, thus opening a window into deep regions of the eukaryotic cell without displaying the shortcomings of previous methods. Although EM methodologies cannot provide live imaging, they can produce snapshots that allow inference of biological transitions. The resolution and number of snapshots have been increasing with the high-throughput automated data collection and analysis. Eva Nogales (University of California–Berkeley, Howard Hughes Medical Institute, and Lawrence Berkeley National Laboratory) reported the structure of GMPCPP and GDP microtubules at 5-A resolution, showing how hydrolysis of GTP results in an accordion-like deformation of protofilaments that is overcome by the presence of Taxol. New developments (silicon-based cameras for direct electron detection, several phase-plate implementations for in-focus EM imaging, and innovative image analysis algorithms) will extend the scope of molecular and cellular EM studies, opening the door for higher-quality structures and quantitative conformational descriptions.

INTRODUCTIONModern applications in the life sciences are frequently based on in vivo imaging of biological specimens, a domain for which light microscopy approaches are typically best suited. Often, quantitative information must be obtained from large multicellular organisms on the cellular or even subcellular level and with a good temporal resolution. However, this usually requires a combination of conflicting features: high imaging speed, low photobleaching, and low phototoxicity in the specimen, good three-dimensional (3D) resolution, an excellent signal-to-noise ratio, and multiple-view imaging capability. The latter feature refers to the capability of recording a specimen along multiple directions, which is crucial for the imaging of large specimens with strong light-scattering or light-absorbing tissue properties. An imaging technique that fulfills these requirements is essential for many key applications: For example, studying fast cellular processes over long periods of time, imaging entire embryos throughout development, or reconstructing the formation of morphological defects in mutants. Here, we discuss digital scanned laser light sheet fluorescence microscopy (DSLM) as a novel tool for quantitative in vivo imaging in the post-genomic era and show how this emerging technique relates to the currently most widely applied 3D microscopy techniques in biology: confocal fluorescence microscopy and two-photon microscopy.

SummaryWe present the Real-time Accurate Cell-shape Extractor (RACE), a high-throughput image analysis framework for automated three-dimensional cell segmentation in large-scale images. RACE is 55–330 times faster and 2–5 times more accurate than state-of-the-art methods. We demonstrate the generality of RACE by extracting cell-shape information from entire Drosophila, zebrafish, and mouse embryos imaged with confocal and light-sheet microscopes. Using RACE, we automatically reconstructed cellular-resolution tissue anisotropy maps across developing Drosophila embryos and quantified differences in cell-shape dynamics in wild-type and mutant embryos. We furthermore integrated RACE with our framework for automated cell lineaging and performed joint segmentation and cell tracking in entire Drosophila embryos. RACE processed these terabyte-sized datasets on a single computer within 1.4 days. RACE is easy to use, as it requires adjustment of only three parameters, takes full advantage of state-of-the-art multi-core processors and graphics cards, and is available as open-source software for Windows, Linux, and Mac OS.