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An ultrathin seal serves as a preventive maintenance technology. The design method predominantly relies on engineering experience and lacks a theoretical foundation. In order to investigate the impact of aggregate size, spreading mass, and original pavement texture depth on the formation of an ultrathin seal, a compaction model was developed using the discrete element method (DEM). Different aggregate sizes and spreading masses were analyzed to examine the particle structure and thickness. The three-dimensional (3D) Weierstrass–Mandelbrot (WM) function was used to reconstruct random rough surfaces to assess the effect of the original pavement texture depth (1, 2, 3, and 4 mm) on voids and dosage of filling asphalt. Results showed that the dynamic compaction led to a rapid increase in collision velocity and then declined sharply by 0.02 s, eventually reaching zero by 0.3 s. Particle contacts steadily increased to 365 by 0.3 s and kept stable after the plateau, indicating the formation of an interlocking structure. Coordination numbers and contact vectors varied with particle size and spreading mass, which were more pronounced for small particles. However, the smaller particles (<4.5 mm) had negligible compaction effects, suggesting that the optimal aggregate size should be 3–5 mm. Excessive spreading mass resulted in a multilayered structure incompatible with the single thickness requirement and the recommended range was 9–12 kg/m2. Furthermore, greater texture depth led to higher void content at the bottom of the seal, requiring more filling asphalt. Therefore, when designing asphalt dosage, both the compaction and the variation in voids due to the original pavement texture depth should be considered to ensure sufficient contacts. [ABSTRACT FROM AUTHOR]

Elbow computerized tomography (CT) scans have been widely applied for describing elbow morphology. To enhance the objectivity and efficiency of clinical diagnosis, an automatic method to recognize, segment, and reconstruct elbow joint bones is proposed in this study. The method involves three steps: initially, the humerus, ulna, and radius are automatically recognized based on the anatomical features of the elbow joint, and the prompt boxes are generated. Subsequently, elbow MedSAM is obtained through transfer learning, which accurately segments the CT images by integrating the prompt boxes. After that, hole-filling and object reclassification steps are executed to refine the mask. Finally, three-dimensional (3D) reconstruction is conducted seamlessly using the marching cube algorithm. To validate the reliability and accuracy of the method, the images were compared to the masks labeled by senior surgeons. Quantitative evaluation of segmentation results revealed median intersection over union (IoU) values of 0.963, 0.959, and 0.950 for the humerus, ulna, and radius, respectively. Additionally, the reconstructed surface errors were measured at 1.127, 1.523, and 2.062 mm, respectively. Consequently, the automatic elbow reconstruction method demonstrates promising capabilities in clinical diagnosis, preoperative planning, and intraoperative navigation for elbow joint diseases. [ABSTRACT FROM AUTHOR]

Elbow computerized tomography (CT) scans have been widely applied for describing elbow morphology. To enhance the objectivity and efficiency of clinical diagnosis, an automatic method to recognize, segment, and reconstruct elbow joint bones is proposed in this study. The method involves three steps: initially, the humerus, ulna, and radius are automatically recognized based on the anatomical features of the elbow joint, and the prompt boxes are generated. Subsequently, elbow MedSAM is obtained through transfer learning, which accurately segments the CT images by integrating the prompt boxes. After that, hole-filling and object reclassification steps are executed to refine the mask. Finally, three-dimensional (3D) reconstruction is conducted seamlessly using the marching cube algorithm. To validate the reliability and accuracy of the method, the images were compared to the masks labeled by senior surgeons. Quantitative evaluation of segmentation results revealed median intersection over union (IoU) values of 0.963, 0.959, and 0.950 for the humerus, ulna, and radius, respectively. Additionally, the reconstructed surface errors were measured at 1.127, 1.523, and 2.062 mm, respectively. Consequently, the automatic elbow reconstruction method demonstrates promising capabilities in clinical diagnosis, preoperative planning, and intraoperative navigation for elbow joint diseases.

Background: In addition to CT images and pathological features, many other molecular characteristics remain unknown about multiple primary lung cancer (MPLC) from intrapulmonary metastatic lung cancer. Case presentation: In this study, we reported a patient with an early-stage MPLC with both adenocarcinoma in situ (AIS) subtype and minimally invasive adenocarcinoma (MIA) subtype. The patient was diagnosed with more than 10 nodules and underwent precise surgery assisted by three-dimensional (3D) reconstruction at the left upper lung lobe. Whole-exome sequencing (WES) and multiple immunohistochemistry (mIHC) were performed to reveal the genomic profiling and tumor microenvironments of multiple nodules in this patient with MPLC. Based on 3D reconstruction location information, we found that the genomic and pathological results of adjacent lymph nodes were quite different. On the other hand, PD-L1 expression and the proportion of infiltrating lymphocytes in tumor microenvironments were all at a low status and did not vary in adjacent lymph nodes. Additionally, maximum diameter and tumor mutational burden levels were found to be significantly associated with CD8+ T cell proportion (p<0.05). Besides, CD163+ macrophages and CD4+ T cell proportion were higher in MIA nodules than in AIS nodules (p<0.05). This patient reached a recurrence-free survival of 39 months. Conclusion: Generally, in addition to CT imaging and pathological results, genomic profiling and tumor microenvironments may facilitate identifying the potential molecular mechanisms and clinical outcomes in patients with earlystage MPLC. [ABSTRACT FROM AUTHOR]

Internal erosion is a phenomenon that fine particles migrate through the channels within coarse matrix under seepage flow. Previous studies mainly focused on the internal erosion under steady hydraulic gradient, while the studies on the behavior and mesoscopic mechanism of internal erosion under fluctuating hydraulic condition were rarely reported. In this study, a setup of transparent soil seepage test was developed. Seepage tests on two types of soils with different internal stability were conducted under steady and fluctuating hydraulic conditions respectively to investigate the internal erosion behaviors under fluctuating hydraulic condition. The macroscopic experimental phenomenon showed that when the hydraulic gradient exceeded the critical value, the hydraulic conductivity under fluctuating hydraulic condition increased faster than that under steady hydraulic condition for internally unstable soil, manifesting that hydraulic fluctuation aggravated the migration of fine particles. In order to further reveal the mesoscopic mechanism, a three-dimensional (3D) reconstruction method was employed to rebuild the mesoscopic fabric of soil based on two-dimensional cross-sectional images obtained by the planar laser scanning; and a 3D visualization digital model including coarse matrix, inter-granular pore channels and fine particles was established. By observing the distribution of fine particles in pore channels, it was found that fine particles might clog and accumulate at narrow pore throats under steady seepage. While the perturbation caused by hydraulic fluctuation could break these weak stable structures of clog and accumulation, and then restart the migration process of fine particles.

BackgroundIn addition to CT images and pathological features, many other molecular characteristics remain unknown about multiple primary lung cancer (MPLC) from intrapulmonary metastatic lung cancer.Case presentationIn this study, we reported a patient with an early-stage MPLC with both adenocarcinoma in situ (AIS) subtype and minimally invasive adenocarcinoma (MIA) subtype. The patient was diagnosed with more than 10 nodules and underwent precise surgery assisted by three-dimensional (3D) reconstruction at the left upper lung lobe. Whole-exome sequencing (WES) and multiple immunohistochemistry (mIHC) were performed to reveal the genomic profiling and tumor microenvironments of multiple nodules in this patient with MPLC. Based on 3D reconstruction location information, we found that the genomic and pathological results of adjacent lymph nodes were quite different. On the other hand, PD-L1 expression and the proportion of infiltrating lymphocytes in tumor microenvironments were all at a low status and did not vary in adjacent lymph nodes. Additionally, maximum diameter and tumor mutational burden levels were found to be significantly associated with CD8+ T cell proportion (p

In cold climates, early-age cementitious material is easily threatened by frost damage, causing deterioration of material properties. To investigate the hazard and failure mechanism of cement paste due to early frost damage, the cement hydration process was divided into five stages via the electrical resistivity method, and then fresh cement pastes were frozen in five stages and two different temperatures, respectively. Furthermore, mechanical tests and X-ray computed tomography scanning were carried out to characterize the development of frost-related damage. The results indicated that the effect of initial frost time on strength growth is greater than that of freezing temperature, and the cement matrix can be considered completely damaged when frost-related damage occurs before the initial setting. The frost-related texture develops from outside to inside and the porosity of the sample frozen at the first three stages was higher than that of samples frozen at the last two stages. Finally, the frost-related damage could be divided into three types: flow extrusion damage, freezing expansion cracking damage, and flow extrusion-freezing expansion cracking combined damage. [ABSTRACT FROM AUTHOR]

The three-dimensional (3D) pore structures and permeability of shale are critical for forecasting gas production capacity and guiding pressure differential control in practical reservoir extraction. However, few investigations have analyzed the effects of microscopic organic matter (OM) morphology and 3D pore nanostructures on the stress sensitivity, which are precisely the most unique and controlling factors of reservoir quality in shales. In this study, ultra-high nanoscale-resolution imaging experiments, i.e. focused ion beam-scanning electron microscopy (FIB-SEMs), were conducted on two organic-rich shale samples from Longmaxi and Wufeng Formations in northern Guizhou Depression, China. Pore morphology, porosity of 3D pore nanostructures, pore size distribution, and connectivity of the six selected regions of interest (including clump-shaped OMs, interstitial OMs, framboidal pyrite, and microfractures) were qualitatively and quantitatively characterized. Pulse decay permeability (PDP) measurement was used to investigate the variation patterns of stress-dependent permeability and stress sensitivity of shales under different confining pressures and pore pressures, and the results were then used to calculate the Biot coefficients for the two shale formations. The results showed that the samples have high OM porosity and 85% of the OM pores have the radius of less than 40 nm. The OM morphology and pore structure characteristics of the Longmaxi and Wufeng Formations were distinctly different. In particular, the OM in the Wufeng Formation samples developed some OM pores with radius larger than 500 nm, which significantly improved the connectivity. The macroscopic permeability strongly depends on the permeability of OM pores. The stress sensitivity of permeability of Wufeng Formation was significantly lower than that of Longmaxi Formation, due to the differences in OM morphology and pore structures. The Biot coefficients of 0.729 and 0.697 were obtained for the Longmaxi and Wufeng Formations, respectively.

Precise documentation of as-is status of transportation infrastructures is an essential task for several public transportation agencies. To tackle this task, such agencies have adopted various advanced technologies, such as light detection and ranging (LiDAR), for three-dimensional (3D) reconstruction and as-built documentation purposes. In this research, we study the feasibility of an alternative 3D reconstruction method, photogrammetry, which has the advantage of being inexpensive and easy to operate compared to LiDAR. To assess the proposed alternative method in transportation asset-inventory collection, this paper evaluates the feasibility of using photogrammetry in providing an acceptable 3D point cloud model of two important categories of transportation assets: roadway assets and pedestrian access ramps. The analysis of the data quality and associated cost attests to the feasibility of using close-range photogrammetry in pedestrian access ramps inventory, while using this technology as a complementary tool with LiDAR in the mobile setting holds the promise for a feasible roadway asset data collection. [ABSTRACT FROM AUTHOR]

Abstract It is difficult to estimate the effective rotation velocity for non‐triaxial stabilized space targets, which leads to deviations in the estimation of imaging plane vectors and azimuth resolution. This makes it hard to reconstruct the three‐dimensional (3D) of space targets based on inverse synthetic aperture radar (ISAR) image sequence. To solve this problem, a joint estimation method of imaging plane vector and 3D structure based on ISAR image sequences is proposed. First, a compact form of imaging plane vector is defined. Then, the 3D structure of a target is characterized by a fully connected deep network. The volume rendering for ISAR images is redesigned with the analysis of projection formula for ISAR imaging. The network is trained using the discrepancy between the modulus of rendered and observed ISAR images in a self‐supervised manner without 3D supervision. And the 3D structure can be obtained by inquiring all points in the 3D space. Therefore, it can optimize imaging planes and produce more complete and accurate results for complex space targets. Adequate simulation experiments verify its superiority.

It is difficult to estimate the effective rotation velocity for non‐triaxial stabilized space targets, which leads to deviations in the estimation of imaging plane vectors and azimuth resolution. This makes it hard to reconstruct the three‐dimensional (3D) of space targets based on inverse synthetic aperture radar (ISAR) image sequence. To solve this problem, a joint estimation method of imaging plane vector and 3D structure based on ISAR image sequences is proposed. First, a compact form of imaging plane vector is defined. Then, the 3D structure of a target is characterized by a fully connected deep network. The volume rendering for ISAR images is redesigned with the analysis of projection formula for ISAR imaging. The network is trained using the discrepancy between the modulus of rendered and observed ISAR images in a self‐supervised manner without 3D supervision. And the 3D structure can be obtained by inquiring all points in the 3D space. Therefore, it can optimize imaging planes and produce more complete and accurate results for complex space targets. Adequate simulation experiments verify its superiority. [ABSTRACT FROM AUTHOR]

High-speed railway in China has undergone rapid development in recent years. Technology for structure measurement is recognized as an important aspect of steel rail quality inspection. The shape of the rail welding base is mainly gauged using mechanical contact measurement technology. Matching this technology with the escalating demands for quality inspection of steel rails is a challenging task. In this paper, a structured light measurement approach is proposed and employed which intersects the rail through the structural light plane projected by inner and outer laser sensors. These sensors form a laser light stripe curve containing the profile information of the rail surface. By processing laser light bars using image analysis and contour reduction techniques, 3-D profiles of the rails are generated. The laser plane is fitted using the coordinate points of the laser light bars converted between the image and world coordinate systems. A new calibration method based on the parallel moving target for line-structured light is proposed to improve the calibration and address the issue caused by the limited number of the extracted calibration points during free target calibration. The rail profile, including the geometric dimension, straightness, and twist of the rail, are then measured. By comparing the measured profile with the standard contour of the rails, the rail wear can then be quantitatively assessed. The experimental results show that the proposed measurement system outperforms the traditional single index detection.

An efficient and accurate forest sample plot survey is of great significance to understand the current status of forest resources at the stand or regional scale and the basis of scientific forest management. Close-range photogrammetry (CRP) technology can easily and quickly collect sequence images with high overlapping to reconstruct the 3D model of forest scenes and extract the individual tree parameters automatically and, therefore, can greatly improve the efficiency of forest investigation and has great application potential in forestry visualization management. However, it has some issues in practical forestry applications. First, the imaging quality is affected by the illumination in the forest, resulting in difficulty in feature matching and low accuracy of parameter extraction. Second, the efficiency of 3D forest model reconstruction is limited under complex understory vegetation or the topographic situation in the forest. In addition, the density of point clouds by dense matching directly affects the accuracy of individual tree parameter extraction. This research collected the sequence images of sample plots of four tree species by smartphones in Gaofeng Forest Farm in Guangxi and Wangyedian Forest Farm in Mongolia to analyze the effects of image enhancement, feature detection and dense point cloud algorithms on the efficiency of 3D forest reconstruction and accuracy of individual tree parameter extraction, then proposed a strategy of 3D reconstruction and parameter extraction suitable for different forest scenes. First, we compared the image enhancement effects of median–Gaussian (MG) filtering, single-scale retinex (SSR) and multi-scale retinex (MSR) filtering algorithms. Then, an improved algorithm combining Harris corner detection with speeded-up robust features (SURF) feature detection (Harris+SURF) is proposed, and the feature matching effect is compared with that of a scale invariant feature transform (SIFT) operator. Third, according to the morphological characteristics of the trees in the sequence images, we used the iterative interpolation algorithm of a planar triangulation network based on geometric constraints (GC-based IIPTN) to increase the density of point clouds and reconstruct the 3D forest model, and then extract the position and DBH of the individual trees. The results show that MSR image enhancement can significantly increase the number of matched point pairs. The improved Harris+SURF method can reduce the reconstruction time of the 3D forest model, and the GC-based IIPTN algorithm can improve the accuracy of individual tree parameter extraction. The extracted position of the individual tree is the same as the measured position with the bias within 0.2 m. The accuracy of extracted DBH of Eucalyptus grandis, Taxus chinensis, Larix gmelinii and Pinus tabuliformis is 94%, 95%, 96% and 90%, respectively, which proves that the proposed 3D model reconstruction method based on image enhancement has great potential for tree position and DBH extraction, and also provides effective support for forest resource investigation and visualization management in the future.

Abstract Objective To evaluate the accuracy of three-dimensional (3D) Cone Beam Computed Tomography (CBCT) and Computed Tomography (CT) reconstructions of human temporal bones compared with in situ measurements. Material and methods Experimental anatomical study of 10 human temporal bones. Wilcoxon's test was used to compare 8 distances on each temporal bone measured in situ and then on 3D CT and CBCT reconstructions. Six landmarks were used: external auditory canal (EAC), tip of the mastoid process, tip of the occiput, zygoma, a point situated 1 cm above the tip of the mastoid process (T0) (open technique: lower limit of the mastoidectomy), head of stapes. Results No significant difference was observed between the 3 measuring techniques for any of the distances studied (P > 0.05). Discussion This study demonstrates the equivalence of CBCT and CT for temporal bone measurements. Conclusion CBCT is a new imaging modality providing 3D reconstructions of the temporal bone that are as reliable as those obtained by CT. As a result of better spatial resolution compared to CT, CBCT is associated with a significantly lower radiation dose. This technique constitutes a morphological progress, as CBCT is comparable to CT, allowing investigation of pathological ears with a lower radiation dose. [ABSTRACT FROM AUTHOR]

To further facilitate the automation and computational efficiency in asphalt mixture micromechanical simulation using finiteelement methods, this paper develops a three-dimensional (3D) microstructural modeling method for asphalt mixture to automatically generate the adaptive 3D finite-element mesh. The methodology contains three main steps, as follows: (1) two-dimensional (2D) enclosed outlines in every X-ray computed tomography (CT) image of the specimens are detected with shape features of outlines and grayscale discrepancy between each two different phase pixels; (2) for each independent geometric solid such as aggregate particle and air void in a specimen, the mapping between the solid and its outlines on various layers is established, so that the 3D model of each solid is constructed; and (3) models of the same phase are assembled into a specific substructure model. The specimen microstructure model is finally obtained with appropriate Boolean operations towards specific substructure models. Experiment results indicate that the specimen microstructure model not only has an excellent accuracy in modeling and simulation, but also supports adaptive meshing toward each specific substructure model, which significantly reduces the computational cost and can be applied to asphalt mixture numerical simulation. [ABSTRACT FROM AUTHOR]

The global scale of point cloud data (PCD) generated through monocular photography and videogrammetry is unknown and can be calculated using at least one known dimension of the scene. Measuring one or more dimensions for this purpose induces a manual step in the three-dimensional reconstruction process; this increases the effort and reduces the speed of reconstructing scenes, and induces substantial human error in the process due to the high level of measurement accuracy needed. Other ways of measuring such dimensions are based on acquiring additional information by either using extra sensors or specific classes of objects existing in the scene; it was found that these solutions are not simple, cost effective, or general enough to be considered practical for reconstructing both indoor and outdoor built infrastructure scenes. To address the issue, this paper proposes a novel method for automatically calculating the absolute scale of built infrastructure PCD. A premeasured cube for outdoor scenes and a sheet of paper for indoor environments are used as the calibration patterns. Assuming that the dimensions of these objects are known, the proposed method extracts the objects' corner points in two-dimensional video frames using a novel algorithm. The extracted corner points are then matched between the consecutive frames. Finally, the corresponding corner points are reconstructed along with other features of the scenes to determine the real-world scale. To evaluate the performance of the method, 10 indoor and 10 outdoor cases were selected and the absolute-scale PCD for each case was computed. Results illustrated the proposed algorithm is able to reconstruct the predefined objects with a high success rate, while the generated absolute-scale PCD is sufficiently accurate. [ABSTRACT FROM AUTHOR]

Simple Summary: We report the first clinical use of Endosight, a new guidance system for percutaneous interventional procedures based on augmented reality, to guide percutaneous thermal ablations. The new system was demonstrated to be precise and reliable, with a targeting accuracy of 3.4 mm. Clinically acceptable, rapid setup and procedural times can be achieved. Background: Over the last two decades, augmented reality (AR) has been used as a visualization tool in many medical fields in order to increase precision, limit the radiation dose, and decrease the variability among operators. Here, we report the first in vivo study of a novel AR system for the guidance of percutaneous interventional oncology procedures. Methods: Eight patients with 15 liver tumors (0.7–3.0 cm, mean 1.56 + 0.55) underwent percutaneous thermal ablations using AR guidance (i.e., the Endosight system). Prior to the intervention, the patients were evaluated with US and CT. The targeted nodules were segmented and three-dimensionally (3D) reconstructed from CT images, and the probe trajectory to the target was defined. The procedures were guided solely by AR, with the position of the probe tip was subsequently confirmed by conventional imaging. The primary endpoints were the targeting accuracy, the system setup time, and targeting time (i.e., from the target visualization to the correct needle insertion). The technical success was also evaluated and validated by co-registration software. Upon completion, the operators were assessed for cybersickness or other symptoms related to the use of AR. Results: Rapid system setup and procedural targeting times were noted (mean 14.3 min; 12.0–17.2 min; 4.3 min, 3.2–5.7 min, mean, respectively). The high targeting accuracy (3.4 mm; 2.6–4.2 mm, mean) was accompanied by technical success in all 15 lesions (i.e., the complete ablation of the tumor and 13/15 lesions with a >90% 5-mm periablational margin). No intra/periprocedural complications or operator cybersickness were observed. Conclusions: AR guidance is highly accurate, and allows for the confident performance of percutaneous thermal ablations. [ABSTRACT FROM AUTHOR]

This paper focuses on the application of a multi- camera imaging system for three-dimensional (3-D) visualization and quantitative characterization of the flame front structures of a turbulent flame. The 2-D images of the flame front are captured simultaneously using identical monochromatic CCD cameras from three different directions around the flame. Dedicated computing algorithms have been developed to reconstruct the 3-D structures of the flame front using various image processing techniques such as edge detection, contour extraction, and mesh generation. A set of flame parameters, including ignition points, ignition volume, ignition surface area, and circularity, is determined from the models generated to characterize the flame front. Results obtained under a range of combustion conditions demonstrate the capability of the system for 3-D quantitative characterization of flame front structures. [ABSTRACT FROM AUTHOR]

An efficient and accurate forest sample plot survey is of great significance to understand the current status of forest resources at the stand or regional scale and the basis of scientific forest management. Close-range photogrammetry (CRP) technology can easily and quickly collect sequence images with high overlapping to reconstruct the 3D model of forest scenes and extract the individual tree parameters automatically and, therefore, can greatly improve the efficiency of forest investigation and has great application potential in forestry visualization management. However, it has some issues in practical forestry applications. First, the imaging quality is affected by the illumination in the forest, resulting in difficulty in feature matching and low accuracy of parameter extraction. Second, the efficiency of 3D forest model reconstruction is limited under complex understory vegetation or the topographic situation in the forest. In addition, the density of point clouds by dense matching directly affects the accuracy of individual tree parameter extraction. This research collected the sequence images of sample plots of four tree species by smartphones in Gaofeng Forest Farm in Guangxi and Wangyedian Forest Farm in Mongolia to analyze the effects of image enhancement, feature detection and dense point cloud algorithms on the efficiency of 3D forest reconstruction and accuracy of individual tree parameter extraction, then proposed a strategy of 3D reconstruction and parameter extraction suitable for different forest scenes. First, we compared the image enhancement effects of median–Gaussian (MG) filtering, single-scale retinex (SSR) and multi-scale retinex (MSR) filtering algorithms. Then, an improved algorithm combining Harris corner detection with speeded-up robust features (SURF) feature detection (Harris+SURF) is proposed, and the feature matching effect is compared with that of a scale invariant feature transform (SIFT) operator. Third, according to the morphological characteristics of the trees in the sequence images, we used the iterative interpolation algorithm of a planar triangulation network based on geometric constraints (GC-based IIPTN) to increase the density of point clouds and reconstruct the 3D forest model, and then extract the position and DBH of the individual trees. The results show that MSR image enhancement can significantly increase the number of matched point pairs. The improved Harris+SURF method can reduce the reconstruction time of the 3D forest model, and the GC-based IIPTN algorithm can improve the accuracy of individual tree parameter extraction. The extracted position of the individual tree is the same as the measured position with the bias within 0.2 m. The accuracy of extracted DBH of Eucalyptus grandis, Taxus chinensis, Larix gmelinii and Pinus tabuliformis is 94%, 95%, 96% and 90%, respectively, which proves that the proposed 3D model reconstruction method based on image enhancement has great potential for tree position and DBH extraction, and also provides effective support for forest resource investigation and visualization management in the future. [ABSTRACT FROM AUTHOR]

Course-based undergraduate research experiences (CUREs) using inquiry-based methodology provide a range of positive benefits to undergraduates and instructors. Yet, the required time and cost in designing and running CUREs with detailed data acquisition steps can lead to barriers in CURE implementation. This report describes an alternative approach to CUREs that utilizes free, open access 3D image volumes as data-rich resources for neurobiology CUREs. These open access image volume CUREs (ivCUREs) effectively combine the data acquisition and analysis steps within the course, allowing more time for students to critically evaluate their hypotheses and results, compare data with peers, and reflect on their experiences. Undergraduates in this 10-week ivCURE analyzed >670 excitatory synapses across two brain areas for the presence and origins of spinules within presynaptic boutons, and fully reconstructed 13 of these synapses in 3D. These data highlight the prevalence of these enigmatic synaptic features within excitatory presynaptic boutons, and their potential importance to neuronal function. Moreover, these results underscore key benefits to ivCURE implementation, including the (1) low-cost of experimental design and implementation, (2) ability to utilize the same data-rich image volume across multiple ivCUREs, (3) potential to generate publishable analyses, and (4) flexibility to scale projects and class sizes up at little to no cost. Opportunities for undergraduates to engage in inquiry-based ivCUREs that examine a host of unexplored questions in neurobiology will continue to grow, in parallel with rapid advances in 3D microscopy techniques and the increased availability and diversity of open access image volumes and analytical tools., (Copyright © 2019 Faculty for Undergraduate Neuroscience.)

Precision and planning are key to reconstructive surgery. Augmented reality (AR) can bring the information within preoperative computed tomography angiography (CTA) imaging to life, allowing the surgeon to 'see through' the patient's skin and appreciate the underlying anatomy without making a single incision. This work has demonstrated that AR can assist the accurate identification, dissection and execution of vascular pedunculated flaps during reconstructive surgery. Separate volumes of osseous, vascular, skin, soft tissue structures and relevant vascular perforators were delineated from preoperative CTA scans to generate three-dimensional images using two complementary segmentation software packages. These were converted to polygonal models and rendered by means of a custom application within the HoloLens™ stereo head-mounted display. Intraoperatively, the models were registered manually to their respective subjects by the operating surgeon using a combination of tracked hand gestures and voice commands; AR was used to aid navigation and accurate dissection. Identification of the subsurface location of vascular perforators through AR overlay was compared to the positions obtained by audible Doppler ultrasound. Through a preliminary HoloLens-assisted case series, the operating surgeon was able to demonstrate precise and efficient localisation of perforating vessels. [ABSTRACT FROM AUTHOR]

There is a rapidly increasing amount of literature outlining the use of three-dimensional (3D) reconstruction and printing technologies in recent years. However, precise instructive articles which describe step-by-step methods of reconstructing 3D images from computed tomography (CT) or magnetic resonance imaging (MRI) remain limited. To address these issues, this article describes a detailed protocol which will allow the reader to easily perform the 3D reconstruction in their future research, to allow investigation of the appropriate surgical anatomy and allow innovative designs of novel screw fixation techniques or pre-operative surgical planning., Competing Interests: Conflicts of Interest: The authors have no conflicts of interest to declare.