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The aim of the study is to assess the efficacy and advantages of utilizing state-of-the-art three-dimensional (3D) reconstruction technology in preoperative planning for rhinoplasty surgery. It is a study of a single rhinoplasty case that was operated at a tertiary hospital. The patient was assessed through a detailed history, blood investigations, radiological investigations and preoperative 3D (three-dimensional) reconstruction of the face and nose. The study utilized high-resolution CT scans and 3D reconstruction software like 3D (three-dimensional) Slicer and Blender 3D (three-dimensional) to analyze nasal anatomy for preoperative planning in rhinoplasty. External and internal nasal measurements were taken, and axial cross-section analysis was conducted to assess nasal structure deviation. The benefits of 3D (three-dimensional) visualization in surgical planning were evaluated, and surgical management was based on preoperative reconstructions. Comprehensive preoperative evaluations were performed, adhering to ethical guidelines. Preoperative 3D (three-dimensional) reconstruction planning methods facilitated precise surgical planning and execution in rhinoplasty with satisfactory outcomes for both the patient and the surgeon. Incorporating 3D (three-dimensional) reconstruction technology in rhinoplasty preoperative planning enhances surgical precision and patient satisfaction, ensuring optimized surgical outcomes while adhering to ethical standards. [ABSTRACT FROM AUTHOR]

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]

The process of air filtration involves the removal of rigid particulates for example dust, pollen, mold, and bacteria from the air. Air cleaners and HVAC (heating, ventilation air conditioning) filters can reduce indoor air pollution; however, frequent maintenance and the replacement of filter media is necessary as per the surrounding atmosphere. HAVC uses nonwoven fabric as its main air filtration media since it provides multiple functions when used in the sub-micron aerosol range. The industry admires advanced ideas, fibers, and filtration media to meet the market demands. The textile nonwoven filtration media having higher efficiency, narrower pore-size distribution, and/or higher dirt-holding capacity are attracting clients' attention. The performance of fabric filters is measured after they are manufactured in the industry. In addition to traditional assessment methods, a quick assessment of such filter media using image processing and computer vision-based approaches is possible. This paper discusses such efforts here. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the growth of the epiphyseal plate in patients with trochlea dysplasia using a 3D computed tomography (CT)-based reconstruction of the bony structure of the distal femur. The epiphysis plate was divided into a medial part and a lateral part to compare their differences in patients with trochlear dysplasia. Methods: This retrospective study included 50 patients with trochlea dysplasia in the study group and 50 age- and sex-matched patients in the control group. Based on the CT images, MIMICS was used to reconstruct the bony structure of the distal femur. Measurements included the surface area and volume of the growth plate (both medial and lateral), the surface area and capacity of the proximal trochlea, trochlea-physis distance (TPD) (both medial and lateral), and height of the medial and lateral condyle. Results: The surface area of the medial epiphyseal plate (1339.8 ± 202.4 mm2 vs. 1596.6 ± 171.8 mm2), medial TPD (4.9 ± 2.8 mm vs. 10.6 ± 3.0 mm), height of the medial condyle (1.1 ± 2.5 mm vs. 4.9 ± 1.3 mm), and capacity of the proximal trochlear groove (821.7 ± 230.9 mm3 vs. 1520.0 ± 498.0 mm3) was significantly smaller in the study group than in the control group. A significant positive correlation was found among the area of the medial epiphyseal plate, the medial TPD, the height of the medial condyle and the capacity of the proximal trochlear groove (r = 0.502–0.638). Conclusion: The medial epiphyseal plate was dysplastic in patients with trochlea dysplasia. There is a significant positive correlation between the surface area of the medial epiphyseal plate, medial TPD, height of the medial condyle and capacity of the proximal trochlear groove, which can be used to evaluate the developmental stage of the trochlea in clinical practice and to guide targeted treatment of trochlear dysplasia. Level of evidence: III. [ABSTRACT FROM AUTHOR]

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]

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]

To ensure the safety and reliability operation of infrastructures, accurate and rapid condition assessment of in-service infrastructures is extremely imperative. Image technologies and techniques, as a non-destructive evaluation (NDE) tool, have created new opportunities to achieve this. It is able to resolve sub-millimeter details including surface flaws and defects, providing a foundation for quantitatively linking observable features to operational performance. This linkage is possible when the quantified feature is directly integrated into tools suitable for describing mechanical response, such as the finite element method. However, the workflow associated with this integration is indirect and presents challenges. This work creates a pathway for a direct scan-to-model strategy suitable for translating condition data derived from a 3D laser scanning system into a computation model capable of describing the mechanical response of the component. The geometric characterization capabilities of the proposed approach and the influence of scan resolution on the geometric characterization are explored. Results of this study provide the foundation of a computational framework for establishing the fundamental link between visually observable geometric changes and the numerical models that engineers use to understand the performance of engineered systems. [ABSTRACT FROM AUTHOR]

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]

Image-based three-dimensional (3D) reconstruction utilizes a set of photos to build 3D model and can be widely used in many emerging applications such as augmented reality (AR) and disaster recovery. Most of existing 3D reconstruction methods require a mobile user to walk around the target area and reconstruct objectives with a hand-held camera, which is inefficient and time-consuming. To meet the requirements of delay intensive and resource hungry applications in 5G, we propose an edge computing-based photo crowdsourcing (EC-PCS) framework in this paper. The main objective is to collect a set of representative photos from ubiquitous mobile and Internet of Things (IoT) devices at the network edge for real-time 3D model reconstruction, with network resource and monetary cost considerations. Specifically, we first propose a photo pricing mechanism by jointly considering their freshness, resolution and data size. Then, we design a novel photo selection scheme to dynamically select a set of photos with the required target coverage and the minimum monetary cost. We prove the NP-hardness of such problem, and develop an efficient greedy-based approximation algorithm to obtain a near-optimal solution. Moreover, an optimal network resource allocation scheme is presented, in order to minimize the maximum uploading delay of the selected photos to the edge server. Finally, a 3D reconstruction algorithm and a 3D model caching scheme are performed by the edge server in real time. Extensive experimental results based on real-world datasets demonstrate the superior performance of our EC-PCS system over the existing mechanisms. [ABSTRACT FROM AUTHOR]

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]

Purpose: The aim of our study was to demonstrate the value of three-dimensional (3D) reconstruction and three-dimensional printing (3DP) models in two cases of soft tissue sarcoma (STS) of the thigh. Materials and methods: Two patients with STS were recruited and underwent enhanced CT and MRI scans. Then, the 3D models were reconstructed and printed using the obtained data, and five experts were invited to assess the segmentation quality. In addition, 34 junior, intermediate and senior general surgeons were recruited to demonstrate the value of 3D models in preoperative planning and invited five surgeons to complete the assessment of 3D models-assisted intraoperative navigation. Finally, 32 interns were enrolled to explore the significance of 3D models in medical education. Results: All experts agree with the accuracy of the 3D models. The application of 3D models in preoperative planning improved the understanding of general surgeons (P = 0.000, P = 0.000, P = 0.000). After the planning tools were exchanged between the two groups, senior surgeons in group A showed more significant improvements in performance than junior and intermediate surgeons in group A (P = 0.001, P = 0.006). Surgeons unanimously agree on the value of 3D models in intraoperative navigation. When applied for the education of medical interns, these models could enhance their understanding of pathologic anatomies (P = 0.036). Conclusion: In two operations for STS of the thigh with complex adjacencies, our study demonstrates that 3D models are of great value for preoperative planning, intraoperative navigation and medical education. More importantly, these models were more helpful to senior general surgeons. [ABSTRACT FROM AUTHOR]

Computer-aided hip surgery planning and implant design applications require accurate segmentation of femoral head and proximal acetabulum. An accurate outer surface extraction of femoral head using marching cubes algorithm remains challenging due to deformed shapes and extremely narrow inter-bone regions. In this paper, we present an automatic and fast approach for segmentation of femoral head and proximal acetabulum which leads to accurate and compact representation of femoral head using marching cubes algorithm. At first, valley-emphasized images are constructed from original images so that valleys stand out in high relief. Otsu's multiple thresholding technique is applied to seperate the images into bone and non-bone classes. Region growing method and threedimensional (3D) morphological operations are performed to fill holes in the bone. In the reclassification process, the bone regions are further segmented, and the boundaries of the bone regions are further refined based on Bayes decision rule. Finally, marching cubes algorithm is applied to reconstruct a 3D model and extract the outer surface of femoral head and proximal acetabulum. Experimental results show that this method is an accurate segmentation technique for femoral head and proximal acetabulum and it can be applied as a tool in medical practice. [ABSTRACT FROM AUTHOR]

The existing three-dimensional (3D) x-ray reconstruction methods for lung cancer tissue reconstruct the investigated objects based on a series of two-dimensional (2D) image sections and a chosen 3D reconstruction algorithm. However, because these procedures apply the same segmentation method for all 2D image sections, they may not achieve the optimal segmentation for each section. As a result, the reconstructed 3D images have limited spatial resolution. Furthermore, the existing 3D reconstruction method is time-consuming and results in a limited time resolution. This research presents an innovation of 3D reconstruction by reformulating two main components of the method. First, a validity index for fuzzy clustering is used to obtain the optimal segmentations of any 2D x-ray image. The process is realized by automatically determining the optimal number of clusters for the image. Second, unlike the existing 3D reconstruction methods, a fast-FCM algorithm is used to speed up the 2D image segmenting process, thereby raising the time resolution of the 3D reconstruction process. With the aid of commonly used VTK software, the proposed method has been used to visualize four classes of typical lung cancer tissues: adenocarcinoma, large cell carcinoma, small cell carcinoma, and squamous cell carcinoma. Experimental results validate the effectiveness and efficiency of the proposed algorithm. Thus, the method contributes a useful tool for x-ray-based 3D image reconstruction. [ABSTRACT FROM AUTHOR]

Adrenocortical carcinoma (ACC) is an extremely rare disease caused by a cancerous growth in the adrenal cortex. Although most of adrenal tumors are benign, the functional ACC is malignant resulting in endocrine dysfunction and necessitates surgical removal. Retroperitoneal laparoscope adrenalectomy is often used to perform adrenal gland surgery. Here, we reported a case of huge ACC with the size of 6.8 cm × 5.2 cm. To achieve better surgical outcome, we integrated 3D reconstructed CT images into a dynamic video for preoperative planning and intraoperative guiding to resect the diseased adrenal gland completely without neighbor organ's injury and surgery complications. Moreover, we reviewed associated applications using 3D reconstructed CT imaging in surgery field. Finally, the evaluation and effect of such technology were discussed to reveal that the 3D dynamic video can help surgeon to make better preoperative assessment so as to give patients better therapy. [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]

This work provides an analysis of the applicability of two image-based three-dimensional (3D) reconstruction techniques-(1) four-dimensional augmented reality () 3D reconstruction software and (2) phototourism applications-for remote site construction project planning. Remote sites present uncertainty to construction project planning through access, material and resource availability, potential lack of technical expertise on site, and environmental considerations. Both and phototourism have the potential to minimize remote site uncertainty by using available camera technology to digitally capture existing site conditions for the development of accurate 3D modeling for construction project planning. For this study, the researchers (1) analyzed the applicability of 3D reconstruction and phototourism software applications to remote construction planning; (2) determined the appropriateness and robustness of various levels of camera technology for capturing existing conditions on remote sites; and (3) evaluated the impact of image resolution and the method of capture on 3D image-based software-all key facets to usability and access. The researchers used three cameras of various performance capabilities, i.e., a 35-mm disposable box camera, a 5.7-17.1-mm (35 mm equivalent: 37-111 mm) low-level digital camera, and a high-level digital single-lens reflex camera. The following paper outlines a methodology for testing these camera technologies and discusses their appropriateness for reducing barriers to the application of image-based reconstruction techniques for remote site construction planning. This work offers the conclusion that ordinary camera technology is an appropriate option for capturing existing conditions in remote sites (usability), while more advanced camera technology offers better total system benefits (access) of the image-based 3D reconstruction platform. offers a more robust system for modeling remote sites; however, both and phototourism have the potential to generate useful computer models using catalogs of digital images to enable better planning and execution of construction projects in remote areas. [ABSTRACT FROM AUTHOR]

Objective: Classic anatomical methods have limitations in micro determination of nerve fibre location. Furthermore, the precise detection of the nerve fibres nature is not possible by means of dissection. The combination of immunohistochemistry and three-dimensional reconstruction could be used to resolve these limitations of morphological sciences. Our aim is to describe the evolution of computer-assisted anatomic dissection (CAAD), which is an original method applied to study the distribution of intra-pelvic nerves in anatomic research. Materials and methods: Serial transverse sectioning of the pelvic region in rabbit, human fetus, infant and adult cadaver was performed. Sections were immuno-histochemically stained and digitized with a high optical resolution scanner. Photoshop 7 software was used in regrouping of the adult cadaver sections then a tri-dimensional reconstruction was achieved using WinSurf software. Results: The 3D reconstruction of the immuno-histochemically stained histologic sections of the pelvis allowed for precise structural identification of the prostate and its innervations (in fetus, infant and adult). In addition, we reconstructed the entire intra-pelvic organs with accurate demonstration of the location of both adrenergic and cholinergic pathways. Moreover, we performed a virtual dissection of each of the pelvic structures with description of the exact location of the inferior hypogastric plexus, as well as the nature and the distribution of its fibres. Conclusion: The CAAD is an original method in anatomic research, which illustrates the fact that descriptive anatomy is still a dynamic science. This method allows for a 3D presentation of the intra-organic innervation, the nature of the nerve fibres, and the distribution of receptors and their neurotransmitters. This technique improves the understanding of the complex anatomic regions such as the pelvis from both surgical and educational point of view. [ABSTRACT FROM AUTHOR]

Although three-dimensional (3D) internal log images are useful to wood scientists for assessing internal log features, little work has been carried out on this subject. The aim of this paper was to demonstrate how two-dimensional (2D) log images may be combined to create 3D images of internal log features. The selected log features include heartwood, sapwood, bark, and knots in a sugar maple log and a black spruce log. The 2D cross-sectional images of the logs were acquired through computed tomography (CT) scanning. For each log, 72 successive 2D cross-sectional CT images of the log were employed to create the corresponding 3D internal log images based on the marching cubes algorithm. The results suggest that the proposed method can produce clear 3D images for each selected internal log features in sugar maple and black spruce. The accuracy analysis of the 3D reconstruction is still a huge challenge and should be fully investigated in future work. [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]

Peroxisomes in the human hepatoblastoma cell line, HepG2, exhibit distinct alterations of shape, size, and distribution, dependent on culture conditions (cell density, duration in culture, and presence of specific growth factors). Although many cells with elongated tubular peroxisomes are present in thinly seeded cultures, spherical particles forming large focal clusters are found in confluent cultures. The authors have analyzed the ultrastructure and the spatial relationship of peroxisomes of HepG2 cells at different stages of differentiation, using three-dimensional (3D)-reconstruction of ultrathin serial sections, and electronic image processing. Cells were prepared for immunofluorescence using different antibodies against peroxisomal matrix and membrane proteins, as well as for electron microscopy after the alkaline 3,3′-diaminobenzidine staining for catalase. The results indicate that the tubular peroxisomes, which can reach a length of several microns, are consistently isolated, and never form an interconnected peroxisomal reticulum. At the time of disappearance of tubular peroxisomes, rows of spherical peroxisomes, arranged like beads on a string, are observed, suggesting fission of tubular ones. In differentiated confluent cultures, clusters of several peroxisomes are seen, which, by immunofluorescence, appear as large aggregates, but after 3D reconstruction consist of single spherical and angular peroxisomes without interconnections. The majority of such mature spherical peroxisomes (but not the tubular ones) exhibit tail-like, small tubular and vesicular attachments to their surface, suggesting a close functional interaction with neighboring organelles, particularly the endoplasmic reticulum, which is often observed in close vicinity of such peroxisomes. [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]

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]