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In this paper, we demonstrate the current concepts in holographic tomography (HT) realized within limited angular range with illumination scanning. The presented solutions are based on the work performed at Warsaw University of Technology in Poland and put in context with the state of the art in HT. Along with the theoretical framework for HT, the optimum reconstruction process and data visualization are described in detail. The paper is concluded with the description of hardware configuration and the visualization of tomographic reconstruction, which is calculated using a provided processing path.

Background and Aims: Alzheimer's disease (AD) is a degenerative neurological condition that worsens over time and leads to deterioration in cognitive abilities, reduced memory, and, eventually, a decrease in overall functioning. Timely and correct identification of Alzheimer's is essential for effective treatment. The systematic study specifically examines the application of deep learning (DL) algorithms in identifying AD using three‐dimensional (3D) imaging methods. The main goal is to evaluate these methods' current state, efficiency, and potential enhancements, offering valuable insights into how DL could improve AD's rapid and precise diagnosis. Methods: We searched different online repositories, such as IEEE Xplore, Elsevier, MDPI, PubMed Central, Science Direct, ACM, Springer, and others, to thoroughly summarize current research on DL methods to diagnose AD by analyzing 3D imaging data published between 2020 and 2024. We use PRISMA (Preferred Reporting Items for Systematic Reviews and Meta‐Analyses) guidelines to ensure the organization and understandability of the information collection process. We thoroughly analyzed the literature to determine the primary techniques used in these investigations and their findings. Results and Conclusion: The ability of convolutional neural networks (CNNs) and their variations, including 3D CNNs and recurrent neural networks, to detect both temporal and spatial characteristics in volumetric data has led to their widespread use. Methods such as transfer learning, combining multimodal data, and using attention procedures have improved models' precision and reliability. We selected 87 articles for evaluation. Out of these, 31 papers included various concepts, explanations, and elucidations of models and theories, while the other 56 papers primarily concentrated on issues related to practical implementation. This article introduces popular imaging types, 3D imaging for Alzheimer's detection, discusses the benefits and restrictions of the DL‐based approach to AD assessment, and gives a view toward future developments resulting from critical evaluation. [ABSTRACT FROM AUTHOR]

Many fields of human activity benefit from the ability to create images of obscured objects placed behind walls and to map their displacement in a noninvasive way. Usually, imaging devices like Synthetic Aperture Radars (SARs) and Ground-Penetrating Radars (GPRs) use expensive dedicated electronics which results in prohibitive prices. This paper presents the experimental implementation and the results obtained from an imaging system capable of performing SAR imaging and interferometric displacement mapping of targets located behind walls, as well as 3D GPR imaging using a low-cost general-purpose radar sensor. The proposed solution uses for the RF section of the system a K-band microwave radar sensor module implementing Frequency-Modulated Continuous Wave (FMCW) operation. The low-cost sensor was originally intended for simple presence detection and ranging for domestic applications. The proposed system was tested in several scenarios and proved to operate as intended for a fraction of the cost of a commercial imaging device. In one scenario, it was able to detect and locate a 15 cm-diameter fire-extinguisher located at a distance of 3.5 m from the scanning system and 1.6 m behind a 3 cm-thick MDF (medium-density fiberboard) wall with cm-level accuracy. In a second test, the proposed system was used to perform interferometric displacement measurements, and it was capable of determining the displacement of a metal case with sub-millimeter accuracy. In a third experiment, the system was used to construct a 3D image of the inside of a wood table with cm-level resolution. [ABSTRACT FROM AUTHOR]

Time of flight is promising technology in machine vision and sensing, with an emerging need for low power consumption, a high image resolution, and reliable operation in high ambient light conditions. Therefore, we propose a novel direct time-of-flight pixel using the single-photon avalanche diode (SPAD) sensor, with an in-pixel averaging method to suppress ambient light and detect the laser pulse arrival time. The system utilizes two orthogonal sinusoidal signals applied to the pixel as inputs, which are synchronized with a pulsed laser source. The detected signal phase indicates the arrival time. To evaluate the proposed system's potential, we developed analytical and statistical models for assessing the phase error and precision of the arrival time under varying ambient light levels. The pixel simulation showed that the phase precision is less than 1% of the detection range when the ambient-to-signal ratio is 120. A proof-of-concept pixel array prototype was fabricated and characterized to validate the system's performance. The pixel consumed, on average, 40 μ W of power in operation with ambient light. The results demonstrate that the system can operate effectively under varying ambient light conditions and its potential for customization based on specific application requirements. This paper concludes by discussing the system's performance relative to the existing direct time-of-flight technologies, identifying their strengths and limitations. [ABSTRACT FROM AUTHOR]

Three-dimensional SAR imaging of urban buildings is currently a hotspot in the research area of remote sensing. Synthetic Aperture Radar (SAR) offers all-time, all-weather, high-resolution capacity, and is an important tool for the monitoring of building health. Buildings have geometric distortion in conventional 2D SAR images, which brings great difficulties to the interpretation of SAR images. This paper proposes a novel Rotating SAR (RSAR) mode, which acquires 3D information of buildings from two different angles in a single rotation. This new RSAR mode takes the center of a straight track as its rotation center, and obtains images of the same facade of a building from two different angles. By utilizing the differences in geometric distortion of buildings in the image pair, the 3D structure of the building is reconstructed. Compared to the existing tomographic SAR or circular SAR, this method does not require multiple flights in different elevations or observations from varying aspect angles, and greatly simplifies data acquisition. Furthermore, both simulation analysis and actual data experiment have verified the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Introduction: Liver cancer presents a growing global health concern, necessitating advanced approaches for intervention. This review investigates the use and effectiveness of software navigation in interventional radiology for liver tumour procedures. Methods: In accordance with Preferred Reporting Items for Systematic reviews and Meta‐Analyses extension for Scoping Reviews (PRISMA‐ScR) guidelines, a scoping review was conducted of the literature published between 2013 and 2023 sourcing articles through MEDLINE, Scopus, CINAHL and Embase. Eligible studies focused on liver cancer, utilised cone‐beam computed tomography (CBCT), and employed software for intervention. Twenty‐one articles were deemed eligible for data extraction and analysis. Results: Categorised by type, software applications yielded diverse benefits. Feeder detection software significantly enhanced vessel identification, reducing non‐target embolisation by up to 43%. Motion correction software demonstrated a 20% enhancement in image quality, effectively mitigating breathing‐induced motion artefacts. Liver perfusion software facilitated efficient tumour targeting while simultaneously reducing the occurrence of side effects. Needle guide software enabled precise radiofrequency ablation needle placement. Additionally, these software applications provided detailed anatomical simulations. Overall, software integration resulted in shorter procedures, reduced radiation exposure and decreased contrast media usage. Conclusion: This scoping review highlights the innovative yet relatively underexplored role of software navigation for liver tumour procedures. The integration of software applications not only enhances procedural efficiency but also bolsters operator confidence, and contributes to improved patient outcomes. Despite the current lack of uniformity and standardisation, these software‐driven advancements hold significant promise for transforming liver tumour interventions. To realise these benefits, further research is needed to explore the clinical impact and optimal utilisation of software navigation tools in interventional radiology. [ABSTRACT FROM AUTHOR]

Nowadays, research focusing on robotics, autonomous vehicles, and scene analysis shows a clear need for the ability to accurately reconstruct three-dimensional environments. One of the methods allowing to conduct such a reconstruction is to use a set of cameras and image processing techniques. This is a passive method. Despite being, in general, less accurate than its active counterparts, it offers significant advantages in numerous applications in which active systems cannot be deployed due to limited performance. This paper provides a theoretical analysis of the accuracy of estimating 3D positions of objects present at a given scene, based on images from a set of cameras. The analysis assumes a known geometrical configuration of the camera system. The important limiting factor in the considered scenario is the physical resolution of sensors-especially in the case of systems that are supposed to work in real time, with a high FPS rate, as the use of high-resolution cameras is difficult in such circumstances. In the paper, the influence of the geometric arrangement of the cameras is studied and important conclusions about the potential of three-camera configurations are drawn. The analysis performed and the formulas derived help predict the boundary accuracy values of any system using a digital camera. The results of an experiment that confirm the theoretical conclusions are presented as well. [ABSTRACT FROM AUTHOR]

We propose a method for multiple-depth extraction in diffraction grating imaging. A diffraction grating can optically generate a diffraction image array (DIA) having parallax information about a three-dimensional (3D) object. The optically generated DIA has the characteristic of forming images periodically, and the period depends on the depth of the object, the wavelength of the light source, and the grating period of the diffraction grating. The depth image can be extracted through the convolution of the DIA and the periodic delta function array. Among the methods for extracting depth images through the convolution characteristics of a parallax image array (PIA) and delta function array, an advanced spatial filtering method for the controllable extract of multiple depths (CEMD) has been studied as one of the reconstruction methods. And that possibility was confirmed through a lens-array-based computational simulation. In this paper, we aim to perform multiple-depth extraction by applying the CEMD method to a DIA obtained optically through a diffraction grating. To demonstrate the application of the CEMD in diffraction grating imaging, a theoretical analysis is performed to apply the CEMD in diffraction grating imaging; the DIA is acquired optically, and the spatial filtering process is performed through computational methods and then compared with the conventional single-depth extraction method in diffraction grating imaging. The application of the CEMD to DIA enables the simultaneous reconstruction of images corresponding to multiple depths through a single spatial filtering process. To the best of our knowledge, this is the first research on the extraction of multiple-depth images in diffraction grating imaging. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a stepping equivalent range-gate method (S-ERG method) to measure the speed and the distance of the moving target for range-gated imaging lidar. In this method, the speed is obtained by recording the time at which the moving target passes the front and back edges of the range gate, the distance information can also be obtained by the front and back edges of the range gate at the same time. To verify the feasibility of this method, a stationary target and a moving target with different speeds were measured by the S-ERG method. By using the S-ERG method, we not only obtained the distance information of the stationary target and the moving target at the front and back edges of the range gate, respectively, but also obtained the speed of the moving target. Compared to speeds measured by rotational displacement sensors, the speed measurement error of the S-ERG method is less than 5%, whether the target is far away or close to the range-gated lidar system, and this method is almost independent of the delay step time. The theoretical analysis and experimental results indicate range-gated imaging lidar using the S-ERG method has high practicality and wide applications. [ABSTRACT FROM AUTHOR]

Ionizing radiation is necessary for diagnostic imaging and deciding the right radiation dose is extremely critical to obtain a decent quality image. However, increasing the dosage to improve the image quality has risks due to the potential harm from ionizing radiation. Thus, finding the optimal as low as diagnostically acceptable (ALADA) dosage is an open research problem that has yet to be tackled using artificial intelligence (AI) methods. This paper proposes a new multi-balancing 3D convolutional neural network methodology to build 3D multidetector computed tomography (MDCT) datasets and develop a 3D classifier model that can work properly with 3D CT scan images and balance itself over the heavy unbalanced multi-classes. The proposed models were exhaustively investigated through eighteen empirical experiments and three re-runs for clinical expert examination. As a result, it was possible to confirm that the proposed models improved the performance by an accuracy of 5% to 10% when compared to the baseline method. Furthermore, the resulting models were found to be consistent, and thus possibly applicable to different MDCT examinations and reconstruction techniques. The outcome of this paper can help radiologists to predict the suitability of CT dosages across different CT hardware devices and reconstruction algorithms. Moreover, the developed model is suitable for clinical application where the right dose needs to be predicted from numerous MDCT examinations using a certain MDCT device and reconstruction technique. [ABSTRACT FROM AUTHOR]

Drilling of a bone surface often occurs in clinical orthopaedic surgery. The position and orientation of the instrument are the most important factors in this process. Theoretically, some mechanical components may assist in orienting an instrument to certain bone shapes, such as the knee joint and caput femoris. However, the mechanical assisting component does not seem to work in some confined spaces where the bone shape is a free-form surface. In this paper, we propose an ingenious hemisphere tabulation method (HTM) for assessing the pose accuracy of an instrument. The acquisition and assessment of HTM is conducted based on an electromagnetic-based stereo imaging method using a custom-made optical measurement unit, and the operation steps of HTM are described in detail. Experimental results based on 50 tests show that the HTM can identify ideal poses and the evaluated pose of an instrument location on a hemisphere model. The mean error of pose localisation is 7.24 deg, with a range of 1.35 to 15.84 and a standard of 3.66 deg, which is more accurate than our previous method. [ABSTRACT FROM AUTHOR]

X-ray phase-contrast micro computed tomography using synchrotron radiation (SR PhC-pCT) offers unique 3D imaging capabilities for visualizing microstructure of the human brain. Its applicability for unstained soft tissue is an area of active research. Acquiring images from a tissue block without needing to section it into thin slices, as required in routine histology, allows for investigating the microstructure in its natural 3D space. This paper presents a detailed step-by- step guideline for imaging unstained human brain tissue at resolutions of a few micrometers with SR PhC-pCT implemented at SYRMEP, the hard X-ray imaging beamline of Elettra, the Italian synchrotron facility. We present examples of how blood vessels and neurons appear in the images acquired with isotropic 5 μιη and 1 μιη voxel sizes. Furthermore, the proposed protocol can be used to investigate important biological substrates such as neuromelanin or corpora amylacea. Their spatial distribution can be studied using specifically tailored segmentation tools that are validated by classical histology methods. In conclusion, SR PhC-pCT using the proposed protocols, including data acquisition and image processing, offers viable means of obtaining information about the anatomy of the human brain at the cellular level in 3D. [ABSTRACT FROM AUTHOR]

The solenoidal large intensity device (SoLID) is a new experimental apparatus planned for Hall A at the Thomas Jefferson National Accelerator Facility (JLab). SoLID will combine large angular and momentum acceptance with the capability to handle very high data rates at high luminosity. With a slate of approved high-impact physics experiments, SoLID will push JLab to a new limit at the QCD intensity frontier that will exploit the full potential of its 12 GeV electron beam. In this paper, we present an overview of the rich physics program that can be realized with SoLID, which encompasses the tomography of the nucleon in 3D momentum space from semi-inclusive deep inelastic scattering, expanding the phase space in the search for new physics and novel hadronic effects in parity-violating DIS, a precision measurement of J / ψ production at threshold that probes the gluon field and its contribution to the proton mass, tomography of the nucleon in combined coordinate and momentum space with deep exclusive reactions, and more. To meet the challenging requirements, the design of SoLID described here takes full advantage of recent progress in detector, data acquisition and computing technologies. In addition, we outline potential experiments beyond the currently approved program and discuss the physics that could be explored should upgrades of CEBAF become a reality in the future. [ABSTRACT FROM AUTHOR]

The paper presents a surface flatness control system designed for installation on a production line. Such a system allows the control of all blanks leaving the production line in terms of measuring flatness made in the conditions prevailing on the production line. The article discusses 3D imaging methods enabling the construction of a surface image. An analysis of imaging parameters for each method is presented. For the selected imaging method, an analysis of the imaging resolution is presented. An example of flatness measurement for a selected element after a welding operation is shown. The flatness measurement algorithm is discussed, and the results of measurements are presented. The results of measurements for selected two product groups are presented. [ABSTRACT FROM AUTHOR]

Seismic reflection utilizes sound waves transmitted into the subsurface, reflected at rock boundaries, and recorded at the surface. Interpretation of their travel times and amplitudes are the key for reconstructing various geomorphological features across geological time (e.g., reefs, dunes, and channels). Furthermore, the integration of surface geomorphology technique mapping, such as digital elevation models, with seismic geomorphology can increase land and marine feature modelling and reduce data uncertainty, as well. This paper presents an overview of seismic and surface geomorphology techniques and proposes an integrated workflow for better geological mapping, 3D surface imaging, and reconstruction. We intend to identify which techniques are more often used and which approaches are more appropriate for better output results. We noticed that an integration of surface and subsurface geomorphology techniques could be beneficial for society in landscape mapping, reservoir characterization, and city/regional planning. [ABSTRACT FROM AUTHOR]

Inline inspection is becoming an essential tool for industrial high-quality production. Unfortunately, the desired acquisition speeds and needs for high-precision imaging are often at the limit of what is physically possible, such as a large field of view at a high spatial resolution. In this paper, a novel light-field and photometry system is presented that addresses this trade off by combining microscopic imaging with special projection optics to generate a parallax effect. This inline microscopic system, together with an image processing pipeline, delivers high-resolution 3D images at high speeds, by using a lateral transport stage changing the optical perspective. Scanning speeds of up to 12 mm/s can be achieved at a depth resolution of 2.8 μm and a lateral sampling of 700 nm/pixel, suitable for inspection in high-quality manufacturing industry. [ABSTRACT FROM AUTHOR]

Photon counting LiDAR can capture the 3D information of long-distance targets and has the advantages of high sensitivity and high resolution. However, the noise counts restrict improvements in the photon counting imaging quality. Therefore, how to make full use of the limited signal counts under noise interference to achieve efficient 3D imaging is one of the main problems in current research. To address this problem, in this paper, we proposes a 3D imaging method for undulating terrain depth estimation that combines constant false alarm probability detection with the Bayesian model. First, the new 3D cube data are constructed by adaptive threshold segmentation of the reconstructed histogram. Secondly, the signal photons are extracted in the Bayesian model, and depth estimation is realized from coarse to fine by the sliding-window method. The robustness of the method under intense noise is proven by sufficient undulating terrain simulations and outdoor imaging experiments. These results show that the proposed method is superior to typical existing methods. [ABSTRACT FROM AUTHOR]

This paper introduces a simple three-dimensional (3D) stereoscopic method using a single unit of an imaging device consisting of a charge-coupled device (CCD) and a zoom lens. Unlike conventional stereoscopy, which requires a pair of imaging devices, 3D surface imaging is achieved by 3D image reconstruction of two images obtained from two different camera positions by scanning. The experiments were performed by obtaining two images of the measurement target in two different ways: (1) by moving the object while the imaging device is stationary, and (2) by moving the imaging device while the object is stationary. Conventional stereoscopy is limited by disparity errors in 3D image reconstruction because a pair of imaging devices is not ideally identical and alignment errors are always present in the imaging system setup. The proposed method significantly reduced the disparity error in 3D image reconstruction, and the calibration process of the imaging system became simple and convenient. The proposed imaging system showed a disparity error of 0.26 in the camera pixel. [ABSTRACT FROM AUTHOR]

Light detection and ranging (LiDAR) technology, a cutting-edge advancement in mobile applications, presents a myriad of compelling use cases, including enhancing low-light photography, capturing and sharing 3D images of fascinating objects, and elevating the overall augmented reality (AR) experience. However, its widespread adoption has been hindered by the prohibitive costs and substantial power consumption associated with its implementation in mobile devices. To surmount these obstacles, this paper proposes a low-power, low-cost, single-photon avalanche detector (SPAD)-based system-on-chip (SoC) which packages the microlens arrays (MLAs) and a lightweight RGB-guided sparse depth imaging completion neural network for 3D LiDAR imaging. The proposed SoC integrates an 8 × 8 SPAD macropixel array with time-to-digital converters (TDCs) and a charge pump, fabricated using a 180 nm bipolar-CMOS-DMOS (BCD) process. Initially, the primary function of this SoC was limited to serving as a ranging sensor. A random MLA-based homogenizing diffuser efficiently transforms Gaussian beams into flat-topped beams with a 45° field of view (FOV), enabling flash projection at the transmitter. To further enhance resolution and broaden application possibilities, a lightweight neural network employing RGB-guided sparse depth complementation is proposed, enabling a substantial expansion of image resolution from 8 × 8 to quarter video graphics array level (QVGA; 256 × 256). Experimental results demonstrate the effectiveness and stability of the hardware encompassing the SoC and optical system, as well as the lightweight features and accuracy of the algorithmic neural network. The state-of-the-art SoC-neural network solution offers a promising and inspiring foundation for developing consumer-level 3D imaging applications on mobile devices. [ABSTRACT FROM AUTHOR]

Contribution: This paper reports a curriculum development in hybrid problem-based learning (h-PBL), addresses the design, implementation, effectiveness, and assessment issues of h-PBL, and explains the mixed results observed regarding the impact of problem-based learning (PBL) on student grades from a hybrid perspective. Background: The effect of PBL on student learning is difficult to analyze. Empirical research on h-PBL has been scant in the engineering education field. Intended Outcomes: The hybrid approach described in this paper can be used to guide other course designs. Future research directions are also provided in order to better capture the positive effects of PBL on student learning. Application Design: A 3-D imaging project was developed and implemented using h-PBL. A non-parametric hypothesis test was conducted to compare four-year student performance data collected after the implementation of h-PBL with four-year student performance data collected under traditional lecturing; both sets of students were taught by the same instructor. Findings: Student project grades improved after h-PBL, whereas student cumulative course grades did not show significant improvement. The study suggests that higher ratios and weights of PBL, better timing in introducing PBL, and more integrated course components in the hybrid approach may further improve student performance. [ABSTRACT FROM AUTHOR]

Planetary, lunar, and deep space exploration has become the frontier of remote sensing science, and three-dimensional (3D) positioning imaging technology is an important part of lunar and deep space exploration. This paper presents a novel passive 3D imaging method based on the photonics integrated interference computational imaging system. This method uses a photonics integrated interference imaging system with a complex lens array. The midpoints of the interference baselines formed by these lenses are not completely overlapped. The distance between the optical axis and the two lenses of the interference baseline are not equal. The system is used to obtain the complex coherence factor of the object space at a limited working distance, and the image evaluation optimization algorithm is used to obtain the clear images and 3D information of the targets of interest. The simulation results show that this method is effective for the working scenes with targets located at single or multiple limited working distances. The sharpness evaluation function of the target presents a good unimodality near its actual distance. The experimental results of the interference of broad-spectrum light show that the theoretical basis of this method is feasible. [ABSTRACT FROM AUTHOR]

The frequency of cleft lip and palate births in Japan is approximately 0.146%. The study aimed to compare the effects of NAM on restoring nasal morphology and improving extraoral nasal morphology in children with cleft lip and palate in the first stage of treatment using 3D imaging and oral model analysis. The subjects were five infants (37.6 ± 14.4 days old) with unilateral cleft lip and palate. The images taken with the 3D analyzer and oral model used for constructing the NAM at the first examination (baseline) and at the completion of the pre-surgical orthodontic treatment (157.8 ± 37.8 days old) were analyzed. The cleft distance was measured at the upper, middle, and lower points on the 3D images. On the model, the cleft jaw width at the maximum protrusion of the healthy and affected sides of the alveolar bone was measured. After the pre-surgical orthopedic treatment, the measured value on the model decreased significantly by a mean of 8.3 mm from baseline, and the cleft lip width narrowed by an average of 2.8 ± 2.2, 4.3 ± 2.3, and 3.0 ± 2.8 mm at the upper, middle, and lower points of the cleft, respectively. Pre-surgical orthopedic treatment using NAM can help narrow the width of the cleft jaw and lip. The sample size is stated at the study limit in the paper. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to present the results of the pilot experiments demonstrating proof of concept of three-dimensional strain elastography, based on freehand ultrasound for the assessment of strain induced by endogenous motion. The technique was tested by inducing pulsatility in an agar-based tissue mimicking phantom with inclusions having different stiffness and scanning the 1D array with an electromagnetic position sensor. The proof of concept is explored with a defined physical phantom and the adopted algorithm for strain analysis. The agar-based phantom was manufactured with two cylindrical inclusions having different stiffness (7 kPa and 75 kPa in comparison to the background 25 kPa) and scattering properties. The internal strain in the phantom was introduced by mimicking a pulsating artery. The agar mixture displacements were estimated by using the GLUE algorithm. The 3D isosurfaces of inclusion from rendered volumes obtained from the B-mode image set and strain elastograms were reconstructed and superimposed for a quantitative comparison. The correspondence between the B-mode image-based inclusion volume and the strain elastography-based volume was good (the Jaccard similarity coefficient in the range 0.64--0.74). The obtained results confirm the 3D freehand endogenous motion-based elastography as a feasible technique. The visualization of the inclusions was successful. However, quantitative measurements showed that the accuracy of the method in volumetric measurements is limited. [ABSTRACT FROM AUTHOR]

Light sheet fluorescence microscope with single light sheet illumination enables rapid 3D imaging of living cells. In this paper we show the design, fabrication and characterization of a diffractive optical element producing several light sheets along a 45° inclined tube. The element, which is based on a multi-focal diffractive lens and a linear grating, generates five thin light sheets with equal intensities when combined with a refractive cylindrical lens. The generated uniform light sheets can be applied for the scanning of samples in tubes enabling flow-driven 3-dimensional imaging. [ABSTRACT FROM AUTHOR]

This paper presents research carried out to assess the accuracy of a fully automatic smartphone-based photogrammetric solution (PhotoMeDAS) to obtain a cranial diagnostic based on the 3D head model. The rigorous propagation of the coordinate measurement uncertainty to the infant's derived cranial deformation indices is demonstrated. The cranial anthropometric parameters and cranial deformation indices that PhotoMeDAS calculates automatically were analysed based on the estimated accuracy and uncertainty. To obtain both accuracy and uncertainty, a dummy head was measured 54 times under different conditions. The same head was measured with a top-of-the-line coordinate-measuring machine (CMM), and the results were used as ground-truth data. It is demonstrated that the PhotoMeDAS 3D models are an average of 1.01 times bigger than the corresponding ground truth, and the uncertainties are around 1 mm. Even assuming uncertainties in the coordinates of up to 1.5 mm, the error in the derived deformation index uncertainties is around 1%. In conclusion, the PhotoMeDAS solution improves the uncertainty obtained in an ordinary paediatric consultation and can be recommended as a tool for doctors to establish an adequate medical diagnosis based on comprehensive cranial deformation indices, which is much more precise and complete than the information obtained by existing analogue devices (measuring tapes and callipers) and easier to use and less expensive than radiological imaging (CT and MRI). [ABSTRACT FROM AUTHOR]

Correlation plenoptic imaging (CPI) is a technique capable of acquiring the light field emerging from a scene of interest, namely, the combined information of intensity and propagation direction of light. This is achieved by evaluating correlations between the photon numbers measured by two high-resolution detectors. Volumetric information about the object of interest is decoded, through data analysis, from the measured four-dimensional correlation function. In this paper, we investigate the relevant aspects of the refocusing algorithm, a post-processing method that isolates the image of a selected transverse plane within the 3D scene, once applied to the correlation function. In particular, we aim at bridging the gap between existing literature, which only deals with refocusing algorithms in case of continuous coordinates, and the experimental reality, in which the correlation function is available as a discrete quantity defined on the sensors pixels. [ABSTRACT FROM AUTHOR]

Circular ground-based SAR (GBSAR) is a new 3D imaging GBSAR with the potential of acquiring high-quality 3D SAR images and 3D deformation. However, its donut-shaped spectrum and short radius of antenna rotation cause high sidelobes on 3D curved surfaces, resulting in 3D SAR images with poor quality. The multi-phase-center circular GBSAR with full array can effectively suppress sidelobes by filling the donut-shaped spectrum to be the equivalent solid spectrum, but it requires a larger number of phase centers, increasing system cost and engineering difficulties. In this paper, a sidelobe suppression method for circular GBSAR 3D imaging based on sparse optimization of radial phase-center distribution is proposed to suppress high sidelobes at low cost. By deriving the point spread function (PSF) of multi-phase-center circular GBSAR and taking the peak sidelobe level (PSL) and integrated sidelobe level (ISL) of the derived PSF as multi-objective functions, we solve the multi-objective optimization problem to optimize the sparse distribution of radial phase centers. The advantage of the proposed method is that the solved optimal radial phase-center distribution can effectively suppress the 3D sidelobes of circular GBSAR with a limited number of phase centers. Finally, the sidelobe suppression effect of the proposed method is verified via 3D imaging simulations. [ABSTRACT FROM AUTHOR]

Polymers are used widely in the power system as insulating materials and are essential to the power grid's security and stability. However, various insulation defects may occur in the polymer., which can lead to severe insulation accidents. Terahertz (THz) detection is a novel non-destructive testing (NDT) method that is able to detect the interface structures inside polymers. The large quantity of information in the THz waveform has potential for the identification of interface types, and the long short-term memory (LSTM) network is one of the most popular artificial intelligence methods for time series data like THz waveform. In this paper, the LSTM classification network was used to identify the internal interfaces of the polymer with the reflected THz pulses of the internal interfaces. The experiment verified that it is feasible to identify and image the void interfaces and impurity interfaces in the polymer using the proposed method. [ABSTRACT FROM AUTHOR]

This paper reports a complete solution for short-acquisition-time, flood-illumination, and non-scanning 3D imaging. Based on an InGaAs/InP 64×64 Geiger-mode avalanche photodiode array, we developed a single-photon imaging Lidar with a field of view of 19.2 mrad. A spatiotemporal dominant imaging method was also applied for depth estimation under high daytime background noise conditions. In the field tests, 3D imaging information was effectively extracted from objects with strong solar background light. An acquisition time of only 0.5 ms to 4 ms was needed for a building target approximately 1300 m away. The experimental results show that the Lidar and its data processing method have the potential for dynamic scenarios that require high performance 3D imaging, such as vehicle navigation, airborne mapping, and moving target monitoring. [ABSTRACT FROM AUTHOR]

Nowadays, research focusing on robotics, autonomous vehicles, and scene analysis shows a clear need for the ability to accurately reconstruct three-dimensional environments. One of the methods allowing to conduct such a reconstruction is to use a set of cameras and image processing techniques. This is a passive method. Despite being, in general, less accurate than its active counterparts, it offers significant advantages in numerous applications in which active systems cannot be deployed due to limited performance. This paper provides a theoretical analysis of the accuracy of estimating 3D positions of objects present at a given scene, based on images from a set of cameras. The analysis assumes a known geometrical configuration of the camera system. The important limiting factor in the considered scenario is the physical resolution of sensors - especially in the case of systems that are supposed to work in real time, with a high FPS rate, as the use of high-resolution cameras is difficult in such circumstances. In the paper, the influence of the geometric arrangement of the cameras is studied and important conclusions about the potential of three-camera configurations are drawn. The analysis performed and the formulas derived help predict the boundary accuracy values of any system using a digital camera. The results of an experiment that confirm the theoretical conclusions are presented as well.

Interferenceless coded aperture correlation holography (I-COACH) provides an alternative way for the 3D imaging of spatial incoherent illuminated or fluorescent sample. However, the low imaging signal-to-noise ratio (SNR) is one of the bottlenecks that restrict the application of I-COACH. The limitation is mainly originated from the strong bias level that presents in the recorded holograms. Phase shifting methods were implemented in I-COACH to eliminate the background noise while the multiple-exposures recording mechanism significantly reduces the temporal resolution of the system. In this paper, we proposed a compressive I-COACH imaging method with high reconstruction quality and without the sacrifice of the imaging speed. The 3D holographic image reconstruction was implemented under compressive sensing framework while only one single-exposure object hologram and one point spread hologram are necessary. High quality reconstructions were obtained using the proposed method, even for the down-sampled holograms. The imaging SNR of the I-COACH system was improved by a factor of more than 16.5% when comparing with the imaging SNR obtained by the conventional cross-correlation reconstruction method. The proposed method provides a fast and high-fidelity imaging method that can potentially benefit the imaging through scattering medium, partial aperture imaging, and other fields. [ABSTRACT FROM AUTHOR]

Lidar imaging systems are one of the hottest topics in the optronics industry. The need to sense the surroundings of every autonomous vehicle has pushed forward a race dedicated to deciding the final solution to be implemented. However, the diversity of state-of-the-art approaches to the solution brings a large uncertainty on the decision of the dominant final solution. Furthermore, the performance data of each approach often arise from different manufacturers and developers, which usually have some interest in the dispute. Within this paper, we intend to overcome the situation by providing an introductory, neutral overview of the technology linked to lidar imaging systems for autonomous vehicles, and its current state of development. We start with the main single-point measurement principles utilized, which then are combined with different imaging strategies, also described in the paper. An overview of the features of the light sources and photodetectors specific to lidar imaging systems most frequently used in practice is also presented. Finally, a brief section on pending issues for lidar development in autonomous vehicles has been included, in order to present some of the problems which still need to be solved before implementation may be considered as final. The reader is provided with a detailed bibliography containing both relevant books and state-of-the-art papers for further progress in the subject. [ABSTRACT FROM AUTHOR]

In this paper, we demonstrate the current concepts in holographic tomography (HT) realized within limited angular range with illumination scanning. The presented solutions are based on the work performed at Warsaw University of Technology in Poland and put in context with the state of the art in HT. Along with the theoretical framework for HT, the optimum reconstruction process and data visualization are described in detail. The paper is concluded with the description of hardware configuration and the visualization of tomographic reconstruction, which is calculated using a provided processing path. [ABSTRACT FROM AUTHOR]

Background: Quantitative imaging of epithelial tissues requires bioimage analysis tools that are widely applicable and accurate. In the case of imaging 3D tissues, a common preprocessing step consists of projecting the acquired 3D volume on a 2D plane mapping the tissue surface. While segmenting the tissue cells is amenable on 2D projections, it is still very difficult and cumbersome in 3D. However, for many specimen and models used in developmental and cell biology, the complex content of the image volume surrounding the epithelium in a tissue often reduces the visibility of the biological object in the projection, compromising its subsequent analysis. In addition, the projection may distort the geometry of the tissue and can lead to strong artifacts in the morphology measurement. Results: Here we introduce a user-friendly toolbox built to robustly project epithelia on their 2D surface from 3D volumes and to produce accurate morphology measurement corrected for the projection distortion, even for very curved tissues. Our toolbox is built upon two components. LocalZProjector is a configurable Fiji plugin that generates 2D projections and height-maps from potentially large 3D stacks (larger than 40 GB per time-point) by only incorporating signal of the planes with local highest variance/mean intensity, despite a possibly complex image content. DeProj is a MATLAB tool that generates correct morphology measurements by combining the height-map output (such as the one offered by LocalZProjector) and the results of a cell segmentation on the 2D projection, hence effectively deprojecting the 2D segmentation in 3D. In this paper, we demonstrate their effectiveness over a wide range of different biological samples. We then compare its performance and accuracy against similar existing tools. Conclusions: We find that LocalZProjector performs well even in situations where the volume to project also contains unwanted signal in other layers. We show that it can process large images without a pre-processing step. We study the impact of geometrical distortions on morphological measurements induced by the projection. We measured very large distortions which are then corrected by DeProj, providing accurate outputs. [ABSTRACT FROM AUTHOR]

Although holography is topic that goes back to the 1950s, the research in this field continues to be very active worldwide. A continuous growth is confirmed by the publication of more than 2000 papers each year in archival journal on different holographic issues. Here we describe shortly what appeared to us to be the most significant achievements reached in 2013 on holographic imaging. [ABSTRACT FROM PUBLISHER]

In this paper, we propose a methodology for generative enhancement of existing 3D image classifiers. This methodology is based on combining the advantages of both non-generative classifiers and generative modeling. Its purpose is to streamline the synthesis of novel deep neural networks by embedding existing compatible classifiers into a generative network architecture. A demonstration of this process and evaluation of its effectiveness is performed using a 3D convolutional classifier and its generative equivalent—a 3D conditional generative adversarial network classifier. The results of the experiments show that the generative classifier delivers higher performance, gaining a relative classification accuracy improvement of 7.43%. An increase of accuracy is also observed when comparing it to a plain convolutional classifier that was trained on a dataset augmented with samples created by the trained generator. This suggests a desirable knowledge sharing mechanism exists within the hybrid discriminator-classifier network. [ABSTRACT FROM AUTHOR]

This paper is devoted to the study of various carbon-based nanomaterials as photoacoustic contrast agents. The research work was performed on agarose-based tissue phantom containing inclusions with and without carbon-based nanomaterials. The inclusion was created with the higher density compared to phantom in order to simulate a tumor. A specially designed photoacoustic probe was introduced for measuring a level of photoacoustic signal and its enhancement caused by the nanoinclusions presence. The probe consists of a buffer for time separation of the signal coming from the excitation source, piezoelectric transducer, and amplifier. A point-by-point measurement of the signal was performed to obtain a two-dimensional map from magnitude of photoacoustic signal and phase delay of the signal registration. From phase delay the 3D photoacoustic images were reconstructed by evaluation of the depth coordinate based on the tissue sound velocity. As an excitation source the light radiation from Nd:YAG laser with a 16 ns pulse duration and a 1064 nm wavelength was used. Firstly, we considered tissue phantom with a tumor covered by graphene oxide as a reference one. It has been shown that the use of graphene oxide leads to significant improvement of the image contrast. Further, the tumors labelled with nanodiamonds (NDs) and carbon fluoroxide (CFO) nanoparticles (NPs) were studied systematically. Amplitude of the photoacoustic signals registered from such tumor phantoms are one order of magnitude lower than the signal ensured by graphene oxide. All three types of the studied carbon-based nanomaterials (GO, NDs, CFO) give stable photoacoustic signal, this allows to consider them as good candidates for further in-vitro experiments in photoacoustic imaging for biological applications. The dependences of the signal level as a function of the NPs concentration were measured for types of NPs. Considering much more efficient penetration of NDs and CFO NPs inside the cells as well as their extremely low cytotoxicity, these both types of carbon nanomaterials could be used for further in-vivo experiments. [ABSTRACT FROM AUTHOR]