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. 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 x 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.

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.

The functional state of a cell is largely determined by the spatiotemporal organization of its proteome. Technologies exist for measuring particular aspects of protein turnover and localization, but comprehensive analysis of protein dynamics across different scales is possible only by combining several methods. Here we describe tandem fluorescent protein timers (tFTs), fusions of two single-color fluorescent proteins that mature with different kinetics, which we use to analyze protein turnover and mobility in living cells. We fuse tFTs to proteins in yeast to study the longevity, segregation and inheritance of cellular components and the mobility of proteins between subcellular compartments; to measure protein degradation kinetics without the need for time-course measurements; and to conduct high-throughput screens for regulators of protein turnover. Our experiments reveal the stable nature and asymmetric inheritance of nuclear pore complexes and identify regulators of N-end rule–mediated protein degradation.

Live imaging of large biological specimens is fundamentally limited by the short optical penetration depth of light microscopes. To maximize physical coverage, we developed the SiMView technology framework for high-speed in vivo imaging, which records multiple views of the specimen simultaneously. SiMView consists of a light-sheet microscope with four synchronized optical arms, real-time electronics for long-term sCMOS-based image acquisition at 175 million voxels per second, and computational modules for high-throughput image registration, segmentation, tracking and real-time management of the terabytes of multiview data recorded per specimen. We developed one-photon and multiphoton SiMView implementations and recorded cellular dynamics in entire Drosophila melanogaster embryos with 30-s temporal resolution throughout development. We furthermore performed high-resolution long-term imaging of the developing nervous system and followed neuroblast cell lineages in vivo. SiMView data sets provide quantitative morphological information even for fast global processes and enable accurate automated cell tracking in the entire early embryo.

High-resolution movies in the Digital Embryo repository
Nature News: "Fruitfly development, cell by cell" by Lauren Gravitz
Nature Methods Technology Feature: "Faster frames, clearer pictures" by Monya Baker
Andor Insight Awards: Life Sciences Winner

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.

A crucial issue in studies of morphogen gradients relates to their range: the distance over which they can act as direct regulators of cell signaling, gene expression and cell differentiation. To address this, we present a straightforward statistical framework that can be used in multiple developmental systems. We illustrate the developed approach by providing a point estimate and confidence interval for the spatial range of the graded distribution of nuclear Dorsal, a transcription factor that controls the dorsoventral pattern of the Drosophila embryo.

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. There is an outstanding potential in applying this technology to the quantitative study of embryonic development. Here, we provide an overview of the different basic implementations of LSFM, review recent technical advances in the field and highlight applications in the context of embryonic development. We conclude with a discussion of promising future directions.

Novel approaches to bio-imaging and automated computational image processing allow the design of truly quantitative studies in developmental biology. Cell behavior, cell fate decisions, cell interactions during tissue morphogenesis, and gene expression dynamics can be analyzed in vivo for entire complex organisms and throughout embryonic development. We review state-of-the-art technology for live imaging, focusing on fluorescence light microscopy techniques for system-level investigations of animal development and discuss computational approaches to image segmentation, cell tracking, automated data annotation, and biophysical modeling. We argue that the substantial increase in data complexity and size requires sophisticated new strategies to data analysis to exploit the enormous potential of these new resources.

Recording light-microscopy images of large, nontransparent specimens, such as developing multicellular organisms, is complicated by decreased contrast resulting from light scattering. Early zebrafish development can be captured by standard light-sheet microscopy, but new imaging strategies are required to obtain high-quality data of late development or of less transparent organisms. We combined digital scanned laser light-sheet fluorescence microscopy with incoherent structured-illumination microscopy (DSLM-SI) and created structured-illumination patterns with continuously adjustable frequencies. Our method discriminates the specimen-related scattered background from signal fluorescence, thereby removing out-of-focus light and optimizing the contrast of in-focus structures. DSLM-SI provides rapid control of the illumination pattern, exceptional imaging quality, and high imaging speeds. We performed long-term imaging of zebrafish development for 58 h and fast multiple-view imaging of early Drosophila melanogaster development. We reconstructed cell positions over time from the Drosophila DSLM-SI data and created a fly digital embryo.