Precise and efficient performance in remote robotic teleoperation relies on intuitive interaction. This requires both accurate control actions and complete perception (vision, haptic, and other sensory feedback) of the remote environment. Especially in immersive remote teleoperation, the complete perception of remote environments in 3D allows operators to gain improved situational awareness. Color and Depth (RGB-D) cameras capture remote environments as dense 3D point clouds for real-time visualization. However, providing enough situational awareness needs fast, high-quality data transmission from acquisition to virtual reality rendering. Unfortunately, dense point-cloud data can suffer from network delays and limits, impacting the teleoperator’s situational awareness. Understanding how the human eye works can help mitigate these challenges. This paper introduces a solution by implementing foveation, mimicking the human eye’s focus by smartly sampling and rendering dense point clouds for an intuitive remote teleoperation interface. This provides high resolution in the user’s central field, which gradually reduces toward the edges. However, this systematic visualization approach in the peripheral vision may benefit or risk losing information and burdening the user’s cognitive load. This work investigates these advantages and drawbacks through an experimental study and describes the overall system, with its software, hardware, and communication framework. This will show significant enhancements in both latency and throughput, surpassing 60% and 40% improvements in both aspects when compared with state-of-the-art research works. A user study reveals that the framework has minimal impact on the user’s visual quality of experience while helping to reduce the error rate significantly. Further, a 50% reduction in task execution time highlights the benefits of the proposed framework in immersive remote telerobotics applications.

In this paper, we propose a comparison of open-source LiDAR and Inertial Measurement Unit (IMU)-based Simultaneous Localization and Mapping (SLAM) approaches for 3D robotic mapping. The analyzed algorithms are often exploited in mobile robotics for autonomous navigation but have not been evaluated in terms of 3D reconstruction yet. Experimental tests are carried out using two different autonomous mobile platforms in three test cases, comprising both indoor and outdoor scenarios. The 3D models obtained with the different SLAM algorithms are then compared in terms of density, accuracy, and noise of the point clouds to analyze the performance of the evaluated approaches. The experimental results indicate the SLAM methods that are more suitable for 3D mapping in terms of the quality of the reconstruction and highlight the feasibility of mobile robotics in the field of autonomous mapping.

The precise structural solution of crystals on a mesostructural scale is challenging due to the difficulties in obtaining electron diffraction and the complicated relationship between the crystal structure factors (CSFs) and the conventional underfocus phase-contrast transmission electron microscopy (TEM) images due to the large unit cell and the complex structures. Here, we present the structural investigation of mesostructured crystals via the combination of electron crystallographic Fourier synthesis and high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) that only relies on the mass-thickness contrast. The three-dimensional electrostatic potential is reconstructed from the amplitudes and phases extracted from the Fourier transforms of the corresponding HAADF-STEM images and merged into a set of CSFs. This method is verified on silica scaffolds following a shifted double-diamond surface network with space group I41/amd. The results indicate that electron crystallography reconstruction by HAADF-STEM images is more suitable and accurate in determining the structure in comparison with conventional TEM electron crystallography reconstruction. This approach transfers the contrast of mesostructured crystals to images more accurately and the relationship between the Fourier transforms of HAADF-STEM images and the CSFs is more intuitive. It shows great advantages for the structural solution of crystals on the mesostructural scale.

Composite, helical nanostructures formed using cooperative interactions of liquid crystals and Au nanoparticles were studied using a scanning transmission electron microscopy (STEM) mode. The investigated helical assemblies exhibit long-range hierarchical order across length scales, as a result of the crystallization (freezing) directed growth mechanism of nanoparticle-coated twisted nanoribbons and their ability to form organized bundles. Here, STEM methods were used to reproduce the 3D structure of the Au nanoparticle double helix.

The last decades have seen a renewed interest in the study of argumentation in archaeology, particularly in response to the overproduction of weak and unreliable interpretations and explanations. Concurrently, recent appeals for scientific transparency and efficiency in the management of archaeological information in digital form have stressed the necessity of explicitly showing the processes followed. A growing body of literature has identified inference to the best explanation (IBE) as the most adequate way of interpreting archaeological data, although it has quietly existed for over a century. Despite this, the investigation of IBE-based models for recording archaeological reasoning remains a largely under-researched topic. The author concludes with a novel IBE-based model for recording archaeological argumentation.

We present a 3D reconstruction method using brightness and camera motion estimation for registering local colon structure in colonoscopy. The proposed method is based on reverse projection from 2D fold contours to 3D space, motion estimation from 3D reconstructed points between neighboring frames, and model registration to reconstruct the fold structure. On the synthetic colon, the average percentages of the reconstructed depth error and circumference error are about 14.2% and 15.2%, respectively. The accuracy is enough for the navigation and control in capsule robot. This work demonstrates that the proposed method is superior to the methods using single-frame-based brightness intensity.

Collagen microstructure is closely related to the mechanical properties of tissues and affects cell migration through the extracellular matrix. To study these structures, three-dimensional (3D) in vitro collagen-based gels are often used, attempting to mimic the natural environment of cells. Some key parameters of the microstructure of these gels are fiber orientation, fiber length, or pore size, which define the mechanical properties of the network and therefore condition cell behavior. In the present study, an automated tool to reconstruct 3D collagen networks is used to extract the aforementioned parameters of gels of different collagen concentration and determine how their microstructure is affected by the presence of cells. Two different experiments are presented to test the functionality of the method: first, collagen gels are embedded within a microfluidic device and collagen fibers are imaged by using confocal fluorescence microscopy; second, collagen gels are directly polymerized in a cell culture dish and collagen fibers are imaged by confocal reflection microscopy. Finally, we investigate and compare the collagen microstructure far from and in the vicinities of MDA-MB 23 cells, finding that cell activity during migration was able to strongly modify the orientation of the collagen fibers and the porosity-related values.

Conventional simultaneous localization and mapping (SLAM) has concentrated on two-dimensional (2D) map building. To adapt it to urgent search and rescue (SAR) environments, it is necessary to combine the fast and simple global 2D SLAM and three-dimensional (3D) objects of interest (OOIs) local sub-maps. The main novelty of the present work is a method for 3D OOI reconstruction based on a 2D map, thereby retaining the fast performances of the latter. A theory is established that is adapted to a SAR environment, including the object identification, exploration area coverage (AC), and loop closure detection of revisited spots. Proposed for the first is image optical flow calculation with a 2D/3D fusion method and RGB-D (red, green, blue + depth) transformation based on Joblove–Greenberg mathematics and OpenCV processing. The mathematical theories of optical flow calculation and wavelet transformation are used for the first time to solve the robotic SAR SLAM problem. The present contributions indicate two aspects: (i) mobile robots depend on planar distance estimation to build 2D maps quickly and to provide SAR exploration AC; (ii) 3D OOIs are reconstructed using the proposed innovative methods of RGB-D iterative closest points (RGB-ICPs) and 2D/3D principle of wavelet transformation. Different mobile robots are used to conduct indoor and outdoor SAR SLAM. Both the SLAM and the SAR OOIs detection are implemented by simulations and ground-truth experiments, which provide strong evidence for the proposed 2D/3D reconstruction SAR SLAM approaches adapted to post-disaster environments.

Colorizing images and representing them in 3D are common practices in many fields of science and industry. Automation of these processes is now bringing new presentation possibilities to scanning electron microscopy (SEM). Here, we discuss various methods used to bring micrographs to life and make details contained within them easier for the human eye to comprehend. These include stereophotogrammetry, reflectometry (“shape from shading”), and a new technique for adding color to objects that soon could make flat, gray SEM images a thing of the past.

An accurate 3D model of an outdoor scene can be used in many different scenarios of precision agriculture, for instance to analyse the silhouette of a tree crown canopy for precision spraying, to count fruit for fruit yield prediction or to simply navigate a vehicle between the plant rows. Instead of using stereovision, limited by the problems of different light intensities, or by using expensive multi-channel 3D range finder (LIDAR scanner), limited by the number of channels, this work investigates the possibility of using two single channel LIDAR scanners mounted on a small robot to allow a real-time 3D object reconstruction of the robot environment. The approach used readings captured by two LIDAR scanners, SICK LMS111 and SICK TiM310, where the first one was scanning horizontally and the second one vertically. In order to correctly map the 3D points of the readings from the vertical sensor into a 3D space, a custom SLAM algorithm based on image registration techniques was used to calculate the new positions of the robot. The approach was tested in an indoor and outdoor environment, proving its accuracy with an error rate of 0.02 m±0.02 m for vertical and −0.01 m±0.13 m for the horizontal plane.

Statoliths are the only hard structures in the gelatinous bell of most scyphozoan medusae and investigations on these structures could promote investigations of the understudied population dynamics and phylogeny of jellyfish. We examined the statoliths of Aurelia aurita jellyfish of different ages by light microscopic and microtomographic measurements supplemented by scanning electron microscopy. The morphometric analyses confirmed that statolith numbers and sizes increase during jellyfish development and revealed that newly-formed statoliths had similar shapes that may change during statolith growth. Nevertheless, most statoliths had a typical compact rod shape with an aspect ratio of 1–2.5 at all ages and we suggest that the composition of statolith shapes may be taxa specific. We developed a new approach allowing exact measurements of statolith growth for the first time. The application of calcein as a fluorescent marker resulted in clear fluorescent lines within the statoliths, allowing calculations of the statolith side face growth increments (0.1 µm/day; n=252). A single-crystal analysis revealed that the calcein incubation did not affect the statolith crystal structure. In conclusion, calcein labeling is an excellent method to follow the growth of bassanite statoliths.

Accuracy of atom probe tomography measurements is strongly degraded by the presence of phases that have different evaporation fields. In particular, when there are perpendicular interfaces to the tip axis in the specimen, layers thicknesses are systematically biased and the resolution is degraded near the interfaces. Based on an analytical model of field evaporated emitter end-form, a new algorithm dedicated to the 3D reconstruction of multilayered samples was developed. Simulations of field evaporation of bilayer were performed to evaluate the effectiveness of the new algorithm. Compared to the standard state-of-the-art reconstruction methods, the present approach provides much more accurate analyzed volume, and the resolution is clearly improved near the interface. The ability of the algorithm to handle experimental data was also demonstrated. It is shown that the standard algorithm applied to the same data can commit an error on the layers thicknesses up to a factor 2. This new method is not constrained by the classical hemispherical specimen shape assumption.

An automated procedure has been developed for the reconstruction of field ion microscopy (FIM) data that maintains its atomistic nature. FIM characterizes individual atoms on the specimen’s surface, evolving subject to field evaporation, in a series of two-dimensional (2D) images. Its unique spatial resolution enables direct imaging of crystal defects as small as single vacancies. To fully exploit FIM’s potential, automated analysis tools are required. The reconstruction algorithm developed here relies on minimal assumptions and is sensitive to atomic coordinates of all imaged atoms. It tracks the atoms across a sequence of images, allocating each to its respective crystallographic plane. The result is a highly accurate 3D lattice-resolved reconstruction. The procedure is applied to over 2000 tungsten atoms, including ion-implanted planes. The approach is further adapted to analyze carbides in a steel matrix, demonstrating its applicability to a range of materials. A vast amount of information is collected during the experiment that can underpin advanced analyses such as automated detection of “out of sequence” events, subangstrom surface displacements and defects effects on neighboring atoms. These analyses have the potential to reveal new insights into the field evaporation process and contribute to improving accuracy and scope of 3D FIM and atom probe characterization.

Nanobelt-like precipitates in an Al–Si–Mg–Hf alloy were studied using electron backscattered diffraction (EBSD) and focused ion beam (FIB) scanning electron microscopy techniques. One grain of the Al matrix with a near [111] normal direction was identified by EBSD and the three-dimensional (3D) microstructure of nanobelt-like precipitates in this grain was studied using 3D-FIB. Ten growth directions of the nanobelt-like precipitates in the grain were identified.

In this study, a combined tilt- and focal series is proposed as a new recording scheme for high-angle annular dark-field scanning transmission electron microscopy (STEM) tomography. Three-dimensional (3D) data were acquired by mechanically tilting the specimen, and recording a through-focal series at each tilt direction. The sample was a whole-mount macrophage cell with embedded gold nanoparticles. The tilt–focal algebraic reconstruction technique (TF-ART) is introduced as a new algorithm to reconstruct tomograms from such combined tilt- and focal series. The feasibility of TF-ART was demonstrated by 3D reconstruction of the experimental 3D data. The results were compared with a conventional STEM tilt series of a similar sample. The combined tilt- and focal series led to smaller “missing wedge” artifacts, and a higher axial resolution than obtained for the STEM tilt series, thus improving on one of the main issues of tilt series-based electron tomography.

Strigomonas culicis (previously referred to as Blastocrithidia culicis) is a monoxenic trypanosomatid harboring a symbiotic bacterium, which maintains an obligatory relationship with the host protozoan. Investigations of the cell cycle in symbiont harboring trypanosomatids suggest that the bacterium divides in coordination with other host cell structures, particularly the nucleus. In this study we used light and electron microscopy followed by three-dimensional reconstruction to characterize the symbiont division during the cell cycle of S. culicis. We observed that during this process, the symbiotic bacterium presents different forms and is found at different positions in relationship to the host cell structures. At the G1/S phase of the protozoan cell cycle, the endosymbiont exhibits a constricted form that appears to elongate, resulting in the bacterium division, which occurs before kinetoplast and nucleus segregation. During cytokinesis, the symbionts are positioned close to each nucleus to ensure that each daughter cell will inherit a single copy of the bacterium. These observations indicated that the association of the bacterium with the protozoan nucleus coordinates the cell cycle in both organisms.

Electron tomography is becoming one of the most used methods for structural analysis at nanometric scale in biological and materials sciences. Combined with chemical mapping, it provides qualitative and semiquantitative information on the distribution of chemical elements on a given sample. Due to the current difficulties in obtaining three-dimensional (3D) maps by energy-filtered transmission electron microscopy (EFTEM), the use of 3D chemical mapping has not been widely adopted by the electron microscopy community. The lack of specialized software further complicates the issue, especially in the case of data with a low signal-to-noise ratio (SNR). Moreover, data interpretation is rendered difficult by the absence of efficient segmentation tools. Thus, specialized software for the computation of 3D maps by EFTEM needs to include optimized methods for image series alignment, algorithms to improve SNR, different background subtraction models, and methods to facilitate map segmentation. Here we present a software package (EFTEM-TomoJ, which can be downloaded from http://u759.curie.fr/fr/download/softwares/EFTEM-TomoJ), specifically dedicated to computation of EFTEM 3D chemical maps including noise filtering by image reconstitution based on multivariate statistical analysis. We also present an algorithm named BgART (for background removing algebraic reconstruction technique) allowing the discrimination between background and signal and improving the reconstructed volume in an iterative way.

Electron tomography (ET) has recently afforded new insights into neuronal architecture. However, the tedious process of sample preparation, image acquisition, alignment, back projection, and additional segmentation process of ET repels beginners. We have tried Hitachi's commercial packages integrated with a Hitachi H-7650 TEM to examine the potential of using an automated fiducial-less approach for our own neuroscience research. Semi-thick sections (200–300 nm) were cut from blocks of fixed mouse (C57BL) cerebellum and prepared for ET. Sets of images were collected automatically as each section was tilted by 2° increments (±60°). “Virtual” image volumes were computationally reconstructed in three dimension (3D) with the EMIP software using either the commonly used “weighted back-projection” (WBP) method or “topography-based reconstruction” (TBR) algorithm for comparison. Computed tomograms using the TBR were more precisely reconstructed compared with the WBP method. Following reconstruction, the image volumes were imported into the 3D editing software A-View and segmented according to synaptic organization. The detailed synaptic components were revealed by very thin virtual image slices; 3D models of synapse structure could be constructed efficiently. Overall, this simplified system provided us with a graspable tool for pursuing ET studies in neuroscience.

At the apical tip of Drosophila testis, there is a stem cell niche known as the proliferation center, where the stem cells are maintained by hub cell cluster for the regulation of differentiation and proliferation. Germline stem cells go through mitosis four times from one primary spermatogonial cell to the 16-cell stage before the maturation. The cells derived from the same germline stem cell are located within one cyst, an enclosed system by two cyst cells, and they are connected by the intercellular bridges called ring canals. In this study, the three-dimensional (3D) structure of Drosophila testis tip was reconstructed from serial sections. The size of cells at each stage was compared in volume from the 3D structure. The stages of cells in a cyst could be distinguishable exactly by counting the cells linked with intercellular bridges in 3D-reconstructed structure. The cysts containing the same stage cells appeared in the horizontal plane. Both the germline stem cell directly attached to the hub cell and the spermatogonial cells detached from the hub cell were divided at the almost perpendicular direction to the spermatogonial cell layers. The dividing phase in one cyst was delayed gradually through the cytoplasmic region of intercellular bridge.