3D Imaging Technology Research Articles

Display Space and Distribution Visualization of Intelligent Algorithms and 3D Interactive Imaging Technology

Display Space and Distribution Visualization of Intelligent Algorithms and 3D Interactive Imaging Technology

One-shot technology for three-dimensional imaging of large animals: perspectives for ruminant management.

In numerous systems of animal production, there is increasing interest in the use of three-dimensional (3D)-imaging technology on farms for its ability to easily and safely measure traits of interest in living animals. With this information, it is possible to evaluate multiple morphological indicators of interest, either directly or indirectly, and follow them through time. Several tools for this purpose were developed, but one of their main weaknesses was their sensitivity to light and animal movement, which limited their potential for large-scale application on farms. To address this, a new device, called Deffilait3D and based on depth camera technology, was developed. In tests on 31 Holstein dairy cows and 13 Holstein heifers, the values generated for most measured indicators were highly repeatable and reproducible, with coefficients of variation lower than 4%. A comparison of measurements obtained from both Deffilait3D and the previous validated system, called Morpho3D, revealed a high degree of similarity for most selected traits, e.g., less than 0.2% variation for animal volume and 1.2% for chest depth, with the highest degree of difference (8%) noted for animal surface area. Previously published equations used to estimate body weight with the Morpho3D device were equally valid using Deffilait3D. This new device was able to record 3D images regardless of the movement of animals and it is affected only by direct daylight. The ongoing step is now to develop methods for automated analysis and extraction from images, which should enable the rapid development of new tools and potentially lead to the large-scale adoption of this type of device on commercial farms.

Scene Polarization 3D Imaging Technology Based on Direction-Aware Network (Invited)

Scene Polarization 3D Imaging Technology Based on Direction-Aware Network (Invited)

The Design and Application of a Polarization 3D Imager for Land Object Imaging

Polarization 3D imaging is a passive, monocular, long-distance 3D imaging technology. Compared with traditional 3D imaging methods, it has many advantages, such as its lack of need for a light source, lack of need for image matching, and ability to achieve 3D imaging using only a single image. In this study, the principle of polarization 3D imaging was introduced. In the design process of a polarization 3D imager, the acquisition method for obtaining polarization information, the extinction ratio, the spatial resolution, and the refractive index of objects was introduced in detail. The influence of these key factors on the accuracy of polarization 3D imaging was analyzed. Taking the limitations of a small satellite payload into account, specific indicators such as multi-aperture polarized imaging, a 10,000:1 extinction ratio, and a spatial resolution of 30 m were designed. The implementation and functions of the polarization 3D imager were elaborated upon, and optical systems and polarizing devices were developed. Finally, by utilizing the image data obtained by the polarization 3D imager, polarization 3D imaging of real ground objects was obtained. The accuracy of the polarization 3D imaging inversion was approximately twice the spatial resolution. These research results lay the technical foundations for the development and practical application of polarization 3D imaging technology and instruments.

High-precision point cloud registration method based on volume image correlation

With the rapid development of binocular reconstruction, fringe projection profilometry, and time of flight, 3D imaging technology has been widely applied in the field of 3D measurement. However, due to limited measurement range and self-occlusion, point cloud registration methods are often used to obtain larger or more complete 3D contours. Although many scholars have proposed various point cloud registration methods, the accuracy and efficiency of point cloud registration still need to be further improved, especially for point clouds with different density or non-rigid transformation. Image registration technology based on image correlation has been developed for many years and has achieved great success in fields such as computer vision, photomechanics, and photogrammetry. Therefore, a simple and direct idea in this paper is to transform the point cloud registration problem into volume image correlation problem. By this, an efficient image registration method based on fast Fourier transform and an inverse compositional Gaussian Newton optimization method that only needs to calculate the Hessian matrix once can be introduced into the point cloud registration field, which can greatly improve the speed and accuracy of point cloud registration. Comparative experiments have shown that our method has doubled the accuracy and efficiency compared to the iterative closest point (ICP) method, and its practicality has also been verified in impeller reconstruction experiments.

Modern tools in congenital heart disease imaging and procedure planning: a European survey.

Congenital heart diseases (CHDs) often show a complex 3D anatomy that must be well understood to assess the pathophysiological consequences and to guide therapy. Three-dimensional imaging technologies have the potential to enhance the physician's comprehension of such spatially complex anatomies. Unfortunately, due to the new introduction in clinical practice, there is no evidence on the current applications. We conducted a survey to examine how 3D technologies are currently used among CHD European centres. Data were collected using an online self-administered survey via SurveyMonkey. The questionnaire was sent via e-mail and the responses were collected between January and June 2022. Ninety-eight centres correctly completed the survey. Of these, 22 regularly perform 3D rotational angiography, 43 have the availability to print in-silico models, and 22 have the possibility to visualize holographic imaging/virtual reality. The costs were mostly covered by the hospital or the department of financial resources. From our survey, it emerges that these technologies are quite spread across Europe, despite not being part of a routine practice. In addition, there are still not enough data supporting the improvement of clinical management for CHD patients. For this reason, further studies are needed to develop clinical recommendations for the use of 3D imaging technologies in medical practice.

3D vs. 2D simulated fetoscopy for spina bifida repair: a quantitative motion analysis

3D imaging technology is becoming more prominent every day. However, more validation is needed to understand the actual benefit of 3D versus conventional 2D vision. This work quantitatively investigates whether experts benefit from 3D vision during minimally invasive fetoscopic spina bifida (fSB) repair. A superiority study was designed involving one expert team (>18 procedures prior) who performed six 2D and six 3D fSB repair simulations in a high-fidelity animal training model, using 3-port access. The 6D motion of the instruments was recorded. Among the motion metrics are total path length, smoothness, maximum speed, the modified Spectral Arc Length (SPARC), and Log Dimensionless Jerk (LDLJ). The primary clinical outcome is operation time (power 90%, 5% significance) using Sealed Envelope Ltd. 2012. Secondary clinical outcomes are water tightness of the repair, CO_2 insufflation volume, and OSATS score. Findings show that total path length and LDLJ are considerably different. Operation time during 3D vision was found to be significantly shorter compared to 2D vision (113pm 9 vs. 149pm 19 min; p = 0.026). These results suggest enhanced performance with 3D vision during interrupted suturing in fetoscopic SBA repair. To confirm these results, a larger-scale follow-up study involving multiple experts and novice surgeons is recommended.

Harnessing 3D-CT Simulation and Planning for Enhanced Precision Surgery: A Review of Applications and Advancements in Lung Cancer Treatment.

The clinical application of three-dimensional computed tomography (3D-CT) technology has rapidly expanded in the last decade and has been applied to lung cancer surgery. Two consecutive reports of large-scale prospective clinical trials from Japan and the United States have brought a paradigm shift in lung cancer surgery and may have led to a rapid increase in sublobar lung resections. Sublobar resection, especially segmentectomy, requires a more precise understanding of the anatomy than lobectomy, and preoperative 3D simulation and intraoperative navigation support it. The latest 3D simulation software packages are user-friendly. Therefore, in this narrative review, we focus on recent attempts to apply 3D imaging technologies, particularly in the sublobar resection of the lung, and review respective research and outcomes. Improvements in CT accuracy and the use of 3D technology have advanced lung segmental anatomy. Clinical applications have enabled the safe execution of complex sublobar resection through a minimally invasive approach, such as video-assisted thoracoscopic surgery and robotic surgery. However, currently, many facilities still render 3D images on two-dimensional monitors for usage. In the future, it will be challenging to further spread and advance intraoperative navigation through the application of 3D output technologies such as extended reality.

Using in-abattoir 3-dimensional measurements from images of beef carcasses for the prediction of EUROP classification grade and carcass weight

Imaging technology can aid the automatic extraction of measurements from beef carcasses, which can be used for objective grading. Many abattoirs, however, rely on manual grading due to the required infrastructure and cost, making technology unfeasible. This study explores 3-dimensional (3D) imaging technology, requiring limited infrastructure, and its ability to predict carcass weight, conformation class and fat class for non-invasive, objective classification. Time-of-flight near-infrared cameras captured 3-dimensional point clouds of beef carcasses, on-line in one commercial abattoir in Scotland, over a 6-month period. Thirty-five 3D images were captured per carcass and processed using machine vison software. Seventy-four measurements were extracted from each point cloud. Removal of extreme outliers resulted in 285,109 datapoints for 17,250 carcasses. Coefficients of variation (CV) for each measurement on a per-animal basis were low and consistent, and measurements were averaged across images. Using a training and validation dataset (70:30), multiple linear regression models predicted EUROP conformation class, fat class, and carcass weight. Stepwise models included fixed effects (sex, breed type, kill date (and cold carcass weight for conformation and fat class)), and 3D image measurements. Including 3D measurements resulted in prediction accuracies of 70%, 50% and 23% for cold carcass weight, conformation, and fat class respectively. Mapping predictions on the traditional EUROP grid used in the UK showed that 99% of conformation classes and 93% of fat classes were classified within the correct or neighbouring grade. The results of this study indicate the potential for non-invasive, in-abattoir technology requiring limited infrastructure to predict carcass traits objectively.

Fully spherical 3D datasets on sedimentary particles: Fast measurement and evaluation

AbstractRecently it became increasingly evident that the statistical distributions of size and shape descriptors of sedimentary particles reveal crucial information on their evolution and may even carry the fingerprints of their provenance as fragments. However, to unlock this trove of information, measurement of traditional geophysical shape descriptors (mostly detectable on 2D projections) is not sufficient; fully spherical 3D imaging and mathematical algorithms suitable to extract new types of inherently 3D shape descriptors are necessary. Available 3D imaging technologies force users to choose either speed or full sphericity. Only partial morphological information can be extracted in the absence of the latter (e.g., LIDAR imaging). In the case of fully spherical imaging, speed was proved to be prohibitive for obtaining meaningful statistical samples, and inherently 3D shape descriptors were not extracted. Here we present a new method by complementing a commercial, portable 3D scanner with simple hardware to quickly obtain fully spherical 3D datasets from large collections of sedimentary particles. We also present software for the automated extraction of 3D shapes and automated measurement of inherently 3D-shape properties. This technique allows for examining large samples without the need for transportation or storage of the samples, and it may also facilitate the collaboration of geographically distant research groups. We validated our software on a large sample of pebbles by comparing previously hand-measured parameters with the results of automated shape analysis. We also tested our hardware and software tools on a large pebble sample in Kawakawa Bay, New Zealand.

95 Predicting Live Body Weight of Beef Heifers Using 3D Imaging

Abstract Accurately measuring body weight (BW) is of great importance for cow-calf producers in the United States, which can lead to better marketing and nutrient management decisions. Traditionally, BW has been recorded using a walk-over scale or approximated by visual observation. Recently, technology has come out that allows BW prediction using three-dimensional (3D) images. The objective of this study was to determine the efficacy of 3D imaging technology as a method to predict BW of beef heifers. Dorsal 3D images were collected on 69 Red Angus/Simmental yearling heifers. Heifers were approximately 12 mo of age that ranged from 282.1 to 440.0 kg of BW. For image collection, a depth camera (Kinect Azure, Microsoft) was placed above the animals, approximately 3 to 4 meters above the floor surface within the alley of a working facility. The image collection software was written in Python (version 3.8) programming language. For a high-quality image to be recorded, heifers needed to be handled in small groups and kept separate. Heifers also needed to have all four feet on the ground and no interference from other animals in the image. Corresponding scale-measured BW were also recorded for each animal concurrent with depth images collection. Heifers were limit fed and weighed in the morning before feeding for both scale measured BW and image collection. The depth images were analyzed using a customized program written in MATLAB (R2022a). Heifer dorsal projected volume was estimated by adding height pixel values that formed the heifer’s dorsal area, excluding the head region. Body weights were regressed from projected heifer body volumes extracted from the depth images, and then metabolic BW (MBW) was calculated using the 0.75 power adjustment of BW. Performance of the prediction model was analyzed using the coefficient of determination (R2) obtained from the regression of projected volume and actual scale BW and the standard error of the mean (SEM) of the predicted BW. Data were analyzed using the PROC REG and PROC CORR procedures in SAS (v9.4). Prediction of BW using image-extracted dorsal projected volume produced an R 2 = 0.89 and SEM = 3.3 kg. When analyzing the correlation of volume to BW, the Pearson correlation coefficient of r = 0.94 (P < 0.0001) was obtained. Regression of projected volume to MBW produced an R 2 = 0.89 and SEM = 0.57 kg. Results show that this model demonstrates the ability to accurately predict BW using depth images projected dorsal volumes on yearling heifers. These results illustrate that 3D images can be used to accurately measure BW of growing heifers that may enhance the ability of cow-calf producers to pro-actively manage grazing livestock.

Single-shot deep-learning based 3D imaging of Fresnel incoherent correlation holography

Fresnel incoherent correlation holography (FINCH) is a non-scanning and non-coherent light 3D imaging technology that has the potential of axial super-resolution imaging. However, the large depth-of-field artifacts of out-of-focus information greatly limits the axial resolution of FINCH. Here, we propose a single-shot deep-learning based 3D imaging method of FINCH. First, a hologram is collected and back propagated to obtain holograms at different back propagation distances. Subsequently, the designed network is used to identify and remove zero-order, conjugate, and defocused image from the hologram, thereby obtaining 3D information of the sample without phase-shifting operation. The experimental results demonstrate that the proposed method can effectively remove the interference of zero-order and conjugate image in back propagation hologram, and the imaging quality is comparable to that of multi-step phase-shifting based FINCH technology. In addition, clear focused images at different distances on the z-axis can be obtained without interference from defocused images at different back propagation distances, indicating that the proposed method can greatly improve temporal and axial resolution of 3D imaging for FINCH.

A consistent methodology for forensic photogrammetry scanning of human remains using a single handheld DSLR camera.

Close-range photogrammetry is an easy, fast, and cheap way to acquire 3D models of human remains of forensic importance.A carefully composed, tested, and systematic photographing procedure has a key role and can greatly increase the quality of photogrammetry models.A photogrammetry-based 3D-digitalization technique could be developed and adopted as part of the daily routine during autopsies.Photogrammetry-based 3D models are much quicker to acquire, look more photorealistic, and are almost as accurate as certain laser scanner-based models.

Abstract 026: Three-dimensional Visualization And Evaluation Of Differences In Renin Expression In Kidneys Exposed In Vivo To Either Low Or High Arterial Pressure

Background: Renin cells are essential for the regulation of blood pressure (BP). In adult mammals, renin cells are present in small numbers in the juxtaglomerular area, but when homeostasis is threatened, such as by hypotension, additional cells along the renal arterioles are recruited to synthesize and release renin. However, there have been no studies to date that have shown changes in the distribution of renin cells in response to changes in BP by three-dimensional (3D) imaging. Objective: Establish a method to visualize and measure renin cells, and comparison of renin expression differences in kidneys exposed to hypo- or hypertension in 3D. Methods: We used our new mouse model ( Ren1 c-tdTomato ) that expresses renin and the fluorescent tdTomato under the control of the endogenous renin gene environment. To test whether we could detect differences in the distribution of renin in response to changes in BP, we subjected Ren1 c-tdTomato mice to aortic coarctation at 3 months of life. The right and left kidneys (RK, LK) are exposed to high and low BPs, respectively. We harvested kidneys after 72 hours and performed tissue-clearing. We used light sheet microscopy for imaging and the Imaris software for 3D reconstruction and data analysis. We defined the 3D renin cell index (3D-RI) as total volume of renin cells (μm 3 ) divided by total number of glomeruli. We extracted 10 cubes of 500 μm square each from the L and R renal cortex, calculated their individual 3D-RI and compared them. Results: With tissue-clearing-based 3D imaging, renin cells were clearly visualized, allowing observation of their distribution and appearance at a one-cell resolution. In the LK exposed to hypotension, several afferent arterioles were identified where renin cells extended close to their branching point. Further, the average value of the 3D-RI was significantly higher in LK (21460 ±6303) than in RK (12838 ± 4632; p = 0.003). Conclusion: Using our new Ren1 c-tdTomato mouse and 3D imaging technology we detected differences in renin cells appearance and distribution in kidneys exposed to hypo- or hypertension. Combined with spatial single cell multiomics, 3D visualization of renin cells will open new avenues for understanding how vascular cells acquire their positional identity in health and disease.

Three-Dimensional Anthropometry for Evaluating Philtrum Contour in Patients With Unilateral Cleft Lip: Comparison Between Photographic Assessment and 3-Dimensional Anthropometry.

Philtrum reconstruction in patients with unilateral cleft lip is a major concern in cheiloplasty. Moreover, a quantitative evaluation of the philtrum contour has not been possible. Advances in 3-dimensional (3D) imaging technology have enabled highly accurate assessments of facial surfaces. This study aimed to justify using 3D anthropometric measurements to quantify traditional photographic grading systems. Sixty-six children with unilateral cleft lip, aged 4 to 6 years (mean age: 69.1±5.7mo), who visited the outpatient clinic from January to December 2020 were included. A plastic surgeon panel graded the philtrum contour using digital photographs, and 3D anthropometry was performed using a 3D imaging system. The philtrum height, philtrum height difference, and dimple depth were measured at the middle of the philtrum. The philtrum height did not show significant changes across the photographic scores ( P =0.06), whereas noticeable differences were observed in the dimple depths based on photographic scores ( P <0.001). The correlation analysis revealed the highest correlation between the photographic score and dimple depth (rho=0.897, P <0.001). The philtrum height on the cleft side (rho=0.478, P <0.001) also correlated with the photographic score, but the correlation was weaker than that of the dimple depth. The dimple depth and philtrum height can help define the philtrum contour. Furthermore, the dimple depth reflects the philtrum contour better and is more suitable as a single parameter. However, relying on a single philtrum height measurement may be insufficient for reliable evaluations, as the relative height from the surrounding tissues is more important than the absolute height measured using 3D anthropometry.

External root resorption and rapid maxillary expansion in the short-term: a CBCT comparative study between tooth-borne and bone-borne appliances, using 3D imaging digital technology

BackgroundThe aim of the study was to analyze and compare external root resorption (ERR) in patients treated with tooth-borne (TB) and bone-borne (BB) rapid maxillary expansion (RME).MethodsThe sample included 40 subjects who received tooth-borne RME (TB group, average age: 13.1 ± 1.08 years) or bone-borne RME (BB group, average age: 14.5 ± 1.11 years) and Cone-beam computed tomography (CBCT) scans before treatment (T0) and after 3-month of retention (T1). A specific 3D Imaging technology was used to generate 3D models of posterior dentition (M1 = maxillary first molars, P2 = second premolars, P1 = first premolar) and calculate volumetric data (mean and percentage values) and shape changes, the latter obtained from deviation analysis between the radicular models at different time points. Evaluation of radicular length changes was performed for each tooth. Data were statistically analysed to perform intra-timing and inter-groups comparisons.ResultsA significant reduction of radicular volume and length was found in posterior dentition in both groups (p < 0.05), and the M1 (volume) and its palatal root (length) were mostly involved in this response. No differences were found between M1, P1 and P2 (p > 0.05) when volumetric changes were calculated as percentage of the total volume. Deviation analysis revealed that the radicular areas mostly affected by shape change were the apex and bucco-medial side. The amount of ERR was significantly greater in TB group compared to BB group.ConclusionsBB-RME treatment could reduce the amount of ERR at the post-expansion stage.

High-Resolution and Wide-Swath 3D Imaging for Urban Areas Based on Distributed Spaceborne SAR

Tomographic synthetic aperture radar (TomoSAR) obtains elevation resolution by adding multiple baselines successively in the direction perpendicular to the line of sight, thereby realizing three-dimensional (3D) reconstruction of complex scenes and significantly promoting the development of the 3D application field. However, a large data redundancy and long mapping time in traditional 3D imaging lead to a large data transmission burden, low efficiency, and high costs. To solve the above problems, this paper proposes a distributed SAR high-resolution and wide-swath (HRWS) 3D imaging technology scheme. The proposed scheme overcomes the size limitation of traditional single-satellite antennas through the multi-channel arrangement of multiple satellites in the elevation direction to achieve HRWS imaging; meanwhile, the distributed SAR system is integrated with tomographic processing technology to realize 3D imaging of difficult areas by using the elevation directional resolution of TomoSAR systems. HRWS 3D SAR increases the baseline length and channel number by transmission in turn, which leads to excessive pulse repetition frequency and causes echoes of different pulse signals to overlap in the same receiving cycle, resulting in range ambiguity and thus seriously affecting the quality of the 3D reconstruction. To solve this problem, this paper proposes a range ambiguity resolution algorithm based on multi-beam forming and verifies it on the measured data from airborne array SAR. Compared with the traditional TomoSAR, the distributed HRWS 3D SAR scheme proposed in this paper can obtain a greater mapping bandwidth with the same resolution in a single flight, thereby enhancing the time correlation, reducing data redundancy, and greatly improving mapping efficiency.

Automated Visual Inspection of Defects in Transparent Display Layers Using Light-Field 3-D Imaging

Since a display panel comprises multiple layered components, defects may occur within different layers through manufacturing processes. Traditional visual inspection systems with a 2D camera cannot identify the occurrence location among layers. Several 3D imaging technologies, such as CT, TSOM, and MRI, suffer from slow performance and a large form factor. In this work, we propose a novel visual inspection method to detect defects on a display panel using light-field 3D imaging. Without powering the target display panel, we first acquire the high-resolution depth information of defects located inside the transparent layers. We then convert the depth information to the object coordinate system to estimate the physical locations of defects. We automatically classify the types of defects and their layer locations along the depth axis in multiple transparent layers of the display panel. Lastly, our experimental results validate that our method can successfully detect and classify various display defects.

Accuracy of digital workflow for placing orthodontic miniscrews using generic and licensed open systems. A 3d imaging analysis of non-native .stl files for guided protocols

BackgroundThis study aimed to assess the accuracy of digital workflow for guided insertion of miniscrews in the anterior palate using restorative implant dentistry software and licensed software for orthodontic applications.MethodsTwenty subjects (8 males, 12 females, mean age = 16.7 ± 2.1 years) were prospectively selected to receive guided insertion of bicortical palatal miniscrews. Virtual planning was performed using restorative implant dentistry software (Blue Sky Plan*, version 4.7) (group 1 = 10 subjects) and licensed orthodontic software (Dolphin Imaging Software, version 11.0) (group 2 = 10 subjects). A specific 3D Imaging technology was applied to permit the registration of the planned and achieved position of the miniscrews based on the superimposition of maxillary models. The angular deviation (accuracy error) between the planned and the achieved positions of the miniscrews were recorded. Independent Student’s test was used with statistical significance set at p value < 0.05.ResultsThe mean accuracy error recorded in group 1 was 7.15° ± 1.09 (right side) and 6.19 ± 0.80 (left side) while the mean error in group 2 was 6.74° ± 1.23 (right side) and 5.79 ± 0.95 (left side). No significant differences were recorded between the two groups (p > 0.05); instead, miniscrews placed on the right side were almost one degree higher than the left side (p < 0.05) in both groups.ConclusionsThe clinical accuracy error was similar when using generic and licensed orthodontic software for guided systems.

Single exposure passive three-dimensional information reconstruction based on an ordinary imaging system

Existing three-dimensional (3D) imaging technologies have issues such as requiring active illumination, multiple exposures, or coding modulation. We propose a passive single 3D imaging method based on an ordinary imaging system. Using the point spread function of the imaging system to realize the non-coding measurement on the target, the full-focus images and depth information of the 3D target can be extracted from a single two-dimensional (2D) image through the compressed sensing algorithm. Simulation and experiments show that this approach can complete passive 3D imaging based on an ordinary imaging system without any coding operations. This method can achieve millimeter-level vertical resolution under single exposure conditions and has the potential for real-time dynamic 3D imaging. It improves the efficiency of 3D information detection, reduces the complexity of the imaging system, and may be of considerable value to the field of computer vision and other related applications.