3D View Research Articles

X-view: Non-egocentric Multi-View 3D Object Detector.

3D object detection algorithms for autonomous driving reason about 3D obstacles either from 3D birds-eye view or perspective view or both. Recent works attempt to improve the detection performance via mining and fusing from multiple egocentric views. Although the egocentric perspective view alleviates some weaknesses of the birds-eye view, the sectored grid partition becomes so coarse in the distance that the targets and surrounding context mix together, which makes the features less discriminative. In this paper, we generalize the research on 3D multi-view learning and propose a novel multi-view-based 3D detection method, named X-view, to overcome the drawbacks of the multi-view methods. Specifically, X-view breaks through the traditional limitation about the perspective view whose original point must be consistent with the 3D Cartesian coordinate. X-view is designed as a general paradigm that can be applied on almost any 3D detectors based on LiDAR with only little increment of running time, no matter it is voxel/grid-based or raw-point-based. We conduct experiments on KITTI [1] and NuScenes [2] datasets to demonstrate the robustness and effectiveness of our proposed X-view. The results show that X-view obtains consistent improvements when combined with mainstream state-of-the-art 3D methods.

Learning a Locally Unified 3D Point Cloud for View Synthesis.

In this paper, we explore the problem of 3D point cloud representation-based view synthesis from a set of sparse source views. To tackle this challenging problem, we propose a new deep learning-based view synthesis paradigm that learns a locally unified 3D point cloud from source views. Specifically, we first construct sub-point clouds by projecting source views to 3D space based on their depth maps. Then, we learn the locally unified 3D point cloud by adaptively fusing points at a local neighborhood defined on the union of the sub-point clouds. Besides, we also propose a 3D geometry-guided image restoration module to fill the holes and recover high-frequency details of the rendered novel views. Experimental results on three benchmark datasets demonstrate that our method can improve the average PSNR by more than 4 dB while preserving more accurate visual details, compared with state-of-the-art view synthesis methods. The code will be publicly available at https://github.com/mengyou2/PCVS.

Depth Map Prediction of Occluded Objects Using Structure Tensor with Gain Regularization

The creation of the 3D rendering model involves the prediction of an accurate depth map for the input images. A proposed approach of a modified semi-global block matching algorithm with variable window size and the gradient assessment of objects predicts the depth map. 3D modeling and view synthesis algorithms could effectively handle the obtained disparity maps. This work uses the consistency check method to find an accurate depth map for identifying occluded pixels. The prediction of the disparity map by semi-global block matching has used the benchmark dataset of Middlebury stereo for evaluation. The improved depth map quality within a reasonable processing time outperforms the other existing depth map prediction algorithms. The experimental results have shown that the proposed depth map predictioncould identify the inter-object boundaryeven with the presence ofocclusion with less detection error and runtime.We observed that the Middlebury stereo dataset has very few images with occluded objects, which made the attainment of gain cumbersome. Considering this gain, we have created our dataset with occlusion using the structured lighting technique. The proposed regularization term as an optimization process in the graph cut algorithm handles occlusion for different smoothing coefficients. The experimented results demonstrated that our dataset had outperformed the Tsukuba dataset regarding the percentage of occluded pixels.

Ensemble of Deep Learning Models for Brain Tumor Detection

In the last two decades, improvement in artificial intelligence and medical imaging technology have made healthcare sector to achieve some remarkable achievements in diseases analysis and prediction. Due to advancement in medical imaging technology the brain images are taken in different modalities, that gives 3D view of different sections of brain for tumor diagnosis. The ability to extract relevant characteristics from magnetic resonance imaging (MRI) scans is a crucial step for brain tumor classifiers. As a result, several studies have proposed various strategies to extract relevant features from different modalities of MRI to predict the growth of abnormal tumor. Most of techniques used conventional techniques of image processing for feature extraction and machine learning for classification. More recently, the use deep learning algorithms in medical imaging has resulted in significant improvements in the classification and diagnosis of brain tumor. Since tumors are located at different regions of brain, the localizing the tumor and classifying it to particular category is challenging task. In this paper, we have solved this problem by designing deep ensemble model. In the proposed approach, first shallow convolutional neural network (SCNN) and VGG16 network were designed with T1C modality MRI image and subsequently loss and accuracy were examined. To improve the performance of model in terms accuracy and loss information, the extracted features from both the deep learning model were fused to improve the classification accuracy of three types of tumors. The obtained results from ensemble deep convolutional neural network model (EDCNN), proved that the fusion of deep learning model improves the accuracy of multiclass classification problem and also tries to address the problem of overfitting of model for imbalance dataset. The proposed model tries to give classification accuracy up to 97.77%. Furthermore, the proposed framework, achieves competitive results when compared with other state of art studies.

Surgical Treatment of Catamenial Chest Pain: Excision of diaphragmatic endometriosis during robot-assisted laparoscopic surgery.

10% of women of reproductive age are affected by endometriosis, and diaphragmatic endometriosis represents 1-1.5% of these cases. Diaphragmatic endometriotic lesions often require surgical treatment. This video aims to demonstrate the appearance of diaphragmatic endometriosis and describe our experience with robot-assisted laparoscopic excision of full thickness diaphragmatic endometriosis. The patient was a 37-year-old female with the complaint of cyclical right shoulder pain (for 1 year). She previously had caesarean section scar and umbilical endometriosis excision procedures. The magnetic resonance imaging (MRI) of the abdomen highlighted three endometriotic nodules, one of which was described as full thickness on the right hemi-diaphragm. The patient underwent a robot-assisted laparoscopic endometriosis surgery as a joint procedure between the gynaecology and general surgery teams. The falciform ligament was completely divided to obtain full views of the endometriotic lesions on the diaphragm. Superficial diaphragmatic lesions were first excised. The larger deep nodule, which was described on the MRI, was then excised with the full thickness of diaphragm. Pleural cavity was entered intentionally to achieve complete excision of the nodule. Laparoscopic assessment of the right lower pleural cavity through this opening did not show any endometriotic lesions. After the excision, the diaphragm was repaired with a barbed suture. Negative pressure suction of the pleural cavity was performed at the end of this repair instead of using a chest tube. The patient was discharged on the 3rd day with no complications encountered. Histopathological examination confirmed endometriosis. The patient was asymptomatic three months after surgery. Robotic-assisted surgery is an easy and safe choice especially in such challenging dual compartment surgeries by providing a 3D view that abolishes sensory loss and increases depth perception, providing better manoeuvrability with tremor absence.

An Integrated Geophysics and Isotope Geochemistry to Unveil the Groundwater Paleochannel in Abydos Historical Site, Egypt

The scientific controversy among archaeologists about the existence of paleochannels under the Abydos archaeological site, Sohag, Egypt connecting the Osirion (cenotaph of Seti I) with the Nile River has been explained in this study. This study is an attempt to address this issue using integrating a near-surface geophysical approach with stable isotopic geochemistry on this site. Particularly, the stable oxygen and hydrogen isotopes on the water samples collected from the surface and the groundwater in the study area were analyzed and interpreted. The isotopes result showed that the Osirion water is a mixture of three different types of water: Old Nile Water (ONW) before the construction of the High Dam, Recent Nile Water (RNW) after the construction of the High Dam, and Paleowater (PW) from deeper aquifers. Field observations of the Osirion and nearby water cannot explain the presence and direction of this water. Therefore, the next step in this study is determining the location and the direction of the paleochannel connecting the Osirion with the Nile River which was proven using the electric resistivity tomography (ERT) technique. By using the results of the isotope of all types of water near the Osirion and its surrounding wells and the water of the Nile River, in addition to the near-surface geophysical measurements, the results indicated that the 3D view of the ERT data revealed a prospective paleochannel in the direction of the northeast and its location, where this channel is in charge of providing groundwater from the Nile River to the Osirion location.

Study on Anti-Inflammatory Mechanism of Angelica pubescens Based on Network Pharmacology and Molecular Docking

References and data show that AP has a certain effect on alleviating inflammation. Based on the methods of network pharmacology and molecular docking, this paper predicts the potential mechanism of anti-inflammatory effect of the effective components. Methods: Active components and target genes of AP were screened out by SymMap, an associated database of TCM syndromes. First, screen out the active components according to the setting conditions, and its molecular structure file was obtained from the PubChem database. The target genes of anti-inflammatory effect were obtained from GeneCards database with “anti-inflammation effect” as the keyword, and then the common gene targets between AP and anti-inflammatory effect were screened. The PPI network diagram was constructed with Cytoscape 3.80 software to screen the core genes. The GO function and KEGG pathway of the core genes were enriched and analyzed by David database; 3D view of proteins encoded by the core gene from the PDB database, conduct molecular docking between the active components and the core proteins in Auto Dock Vina software, and made a heat map with binding free energy. Results: The main anti-inflammatory components were O-Acetylcolumbianetin, isoindigo, Nodakenetin, Marmesin, Diphencyprone; The core targets are TNF, VEGFA, IL6, TP53, IL1B, ESR1, MMP9, PPARG, Jun, CASP3, PTGS2. AP participated in cytokine-mediated signaling pathway, response to drug, positive regulation of gene expression, and other processes by regulating the combination of extracellular space, cell surface with protein and enzyme, and then exert anti-inflammatory activity. The signal pathways mainly involved IL-17 signaling pathway, hepatitis B, TNF signaling pathway, inflammatory bowel disease, rheumatoid arthritis, etc.; Through molecular docking, it was found that the key targets were MMP9, TNF, PTGS2, ESR1, JUN, and PPARG, while the active components which ha,d a strong effect on these genes were O-Acetylcolumbianetin, isoindigo, Nodakenetin, Marmesin, Diphencyprone. Conclusion: This study used network pharmacology and molecular docking methods to predict the potential active components, target genes, and signal pathways of the anti-inflammatory effect of AP, so as to provide a theoretical reference for the follow-up experimental research and clinical treatment of AP.

Application Software Developed for the Determination of Expansion Volume in Clay Soil Generated by the Detonation of an Explosive Charge

Blasting in clay soil in the field of anchoring and foundation of objects and structures has its benefits in construction and geotechnical practice. The foundations of the method lay in the fact that a shock wave is generated when the explosive charge is detonated. The shock wave, with high pressure at the wavefront, causes the natural structure of the clay soil to be destroyed, and a spherical expansion in the clay mass is formed. The presented research is focused on determining the shape and volume of the resulting expansion in test blasts performed with several types of explosives. An application named Borehole was developed to determine the resulting spherical expansion formed after the detonation of an explosive charge with the integration of the GNSS method of measurement, depth camera, and laser. The application Borehole calculates expansion volume based on the coordinates obtained with the GNSS and the laser-obtained distance of the formed expansion and provides a graphical interpretation in 2D and 3D views. Additionally, when developing the application Borehole, compatibility with CAD tools was considered, primarily for better verification and a more detailed graphical interpretation of 3D views. The developed method allows for simple determination of the volume and dimension of the spherical expansion in clay soil with acceptable accuracy for the design and building of geotechnical structures constructed above and underground.

Penggunaan Aplikasi Emaze Sebagai Media Pembelajaran Seni Budaya di SMA Pembangunan Laboratorium UNP

This study aims to describe the use of the Emaze Application as a Learning Medium for Cultural Arts (Dance) at the UNP Laboratory Development High School. This type of research is qualitative research using applied descriptive methods. This research instrument is the researcher himself and is assisted by supporting instruments such as stationery and cameras. The data type uses primary data and secondary data. Data collection techniques are carried out by means of observation, interviews and documentation. The steps of analyzing data are data classification, data clarification, analyzing data, describing data and inferring data. The results showed that the use of the Emaze application as a medium for learning cultural arts (dance) in class X of the UNP Laboratory Development High School is very helpful for educators in delivering material to students more structured and interesting. Students' learning motivation increases with the 3D view and other advantages of the Emaze application. This can be seen from the results of student practice exams that are very satisfactory and achieve learning objectives in accordance with the syllabus and rpp. Teachers really appreciate the use of the Emaze application and are excited to learn to use the Emaze application in order to be able to use it when teaching and students like and are even interested in using the Emaze application again during learning using the discussion method. However, not all students expressed this, there are also those who are opposed to the above statement but the number who support the use of the Emaze application is very far from those who do not support it.

Adoption of otolaryngologist-head neck surgeons toward transoral robotic surgery: An international survey.

To investigate perception, adoption and awareness of otolaryngologist-head neck surgeons (OTO-HNS) toward transoral robotic surgery (TORS). An online survey was sent to 1383 OTO-HNS on the perception, adoption and awareness about TORS to members of many otolaryngological societies. The following aspects were assessed: TORS access; training; awareness/perception; indications and advantages/barriers to TORS practice. The responses were presented for the entire cohort and regarding the TORS experience of OTO-HNS. A total of 359 completed the survey (26%); including 115 TORS surgeons. TORS-surgeons carry out a mean number of 34.4 annual TORS procedures. The primary barriers to TORS were the cost of the robot (74%) and disposable accessories (69%), and the lack of training opportunity (38%). The 3D view of the surgical field (66%), the postoperative quality of life outcomes (63%) and the shorter hospital stay (56%) were the most important benefits of TORS. TORS-surgeons believed more frequently that TORS is indicated for cT1-T2 oropharyngeal and supraglottic cancers than non-TORS surgeons (p < .005). Participants believed that the priorities for the future consisted of the reduction of the robot arm size and the incorporation of flexible instruments (28%); the integration of laser (25%) or GPS tracking based on imaging (18%), all of them to improve accesses to hypopharynx (24%), supraglottic larynx (23%) and vocal folds (22%). The perception, adoption and knowledges toward TORS depend on the access to robot. The findings of this survey may help guide decisions on how improve the dissemination of TORS interest and awareness.

Improving Big Data Analytics With Interactive Augmented Reality

Since, data is generated every minute by everyone including consumers and/or business worldwide, there is an enormous worth for big data analytics. Big data analytics is a technique for extracting important information from large amounts of a data. Visualization is the best medium to analyze and share information. Visual images help to transmit bid data to the human brain within a few seconds. Visual interpretations help in visualizing data from different angles. Visualization helps to outline problems and understand current trends. Augmented reality enables the user to experience the real world, which is digitally augmented in a way. The main objective of this research work is to find the solution to visualize the analyzed data and show it to the users in a 3D view and to improve the angle of visualization with the help of augmented reality techniques.

A New Set of 3D Shifted Fractional-Order Gegenbauer Descriptors for Volumetric Image Representation

Volumetric images have a three-dimensional (3D) view, in which viewers can examine their characteristics from any angle. The more accurate the digital representation of volumetric images, the more precise and valuable the assessment of what these images represent. The representation of volumetric images is a significant area of study in pattern recognition and computer vision. Recently, volumetric image analysis using orthogonal moments with fractional order has opened up a new study pathway, which has led scholars to discover many real-life applications through investigating efficient algorithms to represent the features of 3D images. In this study, a new set of 3D shifted fractional-order Gegenbauer moments (FrGMs) for volumetric image representation is proposed. First, a mathematical description of the shifted Gegenbauer moments for 3D images is presented. Second, a fast, highly accurate method for calculating the fractional-order shifted Gegenbauer moments of 3D images is introduced. Finally, the efficiency of the proposed FrGMs is evaluated through various suitable experiments and compared with existing methods in terms of the reconstruction of 3D images, the invariability property, sensitivity to noise, and computation time. The experimental results clearly show that FrGMs outperform existing related algorithms.

A Comparison of Diagnostic Accuracy of Imaging Modalities to Detect Optic Disc Drusen: The Age of Enhanced Depth Imaging Optical Coherence Tomography

To identify the most accurate diagnostic imaging modality to detect optic disc drusen (ODD) between B-scan ultrasonography (US), fundus photography, fundus autofluorescence (FAF), and enhanced depth imaging optical coherence tomography (EDI-OCT). Comparative diagnostic analysis. Two hundred five eyes of 105 patients referred to 2 tertiary care neuro-ophthalmology clinics for suspected ODD were recruited: 108 eyes had ODD and 97 did not have ODD. All eyes received a full in-person ophthalmic exam with 3D view of the optic nerve and all 4 imaging modalities. Images were independently reviewed by 3 masked neuro-ophthalmologists to determine the presence or absence of ODD. Final interpretation was made through consensus. The reference standard was defined as the attending ophthalmologist's clinical judgement based on open chart review, with access to all image modalities and clinical information, including disease course. Main outcome measures were sensitivity, specificity, accuracy, and precision for each imaging modality. Examiner confidence was quantified as the proportion of eyes in which the reviewers were certain of their decision. The EDI-OCT had the highest sensitivity and accuracy (95%, 97%) to detect ODD, compared with FAF (84%, 92%), US (74%, 86%), and fundus photography (38%, 66%), respectively. All image modalities had high specificity (> 97%) and precision (> 93%). The EDI-OCT also had highest examiner confidence (96%) compared with all others (88%). Among all modalities, EDI-OCT was the imaging modality with the highest diagnostic utility for the detection of ODD and should be considered as the preferred initial diagnostic modality.

On the investigation of optical soliton solutions of cubic–quartic Fokas–Lenells and Schrödinger–Hirota equations

Purpose:When it comes to third and higher-order dispersion, the Schrödinger–Hirota equation is one of the main models developed outside the classical NLSE management models for optical soliton transmission. The cubic–quartic Fokas–Lenells equation is also one of the recently developed equations, which has importance in the field of telecommunications regarding optical soliton transmission in the absence of chromatic dispersion. In this study, in order to examine the optical solitons, the Schrödinger–Hirota equation in the presence of the chromatic dispersion and the cubic–quartic Fokas–Lenells equation discarding the chromatic dispersion were investigated. For this intent, by obtaining certain soliton types using the unified Riccati equation expansion method (UREEM), optical soliton solutions were obtained for both models and graphical representations and comments were made. Methodology:By developing appropriate computer algorithms and applying UREEM in the following ways, symbolic calculation software was made and analytical optical soliton solutions were obtained. Findings:Through computer algebra software, we plotted the obtained results via 3D, 2D views and we also illustrated the investigation of wave behavior caused by parameter change on 2D graphics. Originality:Different soliton behavior under the parameters effect of the Schrödinger–Hirota equation having chromatic dispersion and the cubic–quartic Fokas-Lenells equation is investigated and the obtained results are reported.

A GIS-based Methodology to Explore and Manage the Historical Heritage of Rabat City (Morocco)

The management of cultural heritage in Morocco is considered as a lever for local development. It constitutes an economic and social challenge of great value. Also, it is at the heart of the debate on tourism development and raises many questions about its preservation and valorization. This article is part of the implementation of a database of the historical heritage of Rabat city (Capital of Morocco) using the Geographic Information System (GIS), which will allow access to information and therefore the protection of this heritage. Indeed, only a rigorous inventory and periodic inventory of the cultural assets allows us to know its extent, assess its importance and specificity, prevent threats to archaeological sites and remains, and ensure the management of research. This systematic study consists of collecting and managing archaeological, textual, iconographic, and photographic information and documentation to create an archaeological database or thematic maps, and to provide a 3D view of these assets. Also, to evaluate the carrying capacity at the archaeological site of Chellah. Through our methodology, we have established an exhaustive inventory of the monuments and sites of Rabat city. Each site has been described, to evaluate its potentialities and historical phases, as well as an inventory of sites and heritage protection areas including adobe buildings.

About Segmath, a new Cerebral Vascular Segmentation Software after CTA

Objectives: The new segmentation software Segmath delivers a 3D view of the cerebral vascular structures without superposition of bony or other structures. This will, according to the literature, improve the workflow of stroke patients and increase the occlusion detection rate on the original CTA. Materials and methods: The software written in MATLAB is based on the analysis of the local Hessian matrix with new original functions of the resulting local eigenvalues. No user intervention in the segmentation process is needed. Results: The validation of the new software yields good results both with synthetic data and real CTA’s. Conclusion: This segmentation software is a powerful additional diagnostic tool available to radiologists and neurologists examining and treating stroke patients. This will improve the workflow of suspected stroke patients.

Structure and Present State of the Astroni Volcano in the Campi Flegrei Caldera in Italy Based on Multidisciplinary Investigations

AbstractDespite its known reconstructed volcanic history, the structural setting and present state of the Astroni Volcano of the Campi Flegrei caldera in Italy are still poorly defined. Through structural, geophysical, and geochemical investigations, we elucidate the structure and present volcanic activity of the Astroni Volcano, which hosts tuff cones, scoriae cones, lava domes, and lakes on the crater floor. A volcano‐tectonic analysis focused on the entire volcano edifice, coupled with electrical resistivity tomography of the shallower part of the Astroni crater, revealed the main rock formations, faults, and possible fluid patterns within the first 150 m depth. Two main NE–SW and NW–SE trending fault sets were imaged using electrical resistivity modeling and measurements along the wall of the volcanic edifice; they likely delimit a maar‐like structure resulting from the highest energetic subplinian Astroni 6 eruption event and acted as magma pathways during the late eruptive activity stage. A 3D view of the reconstructed resistivity model revealed both deep root‐conduit‐like structures and shallower dome‐like shapes for volcanic edifices on the crater floor. Gas and carbon compositions in the NNE sectors of the Astroni Lago Grande are similar to those of the Solfatara fumarole fluids, suggesting common hydrothermal origin and a possible link with a deep hydrothermal reservoir. This fluid‐emission area along the border of the younger volcanic structure exhibits a +40°C maximum soil‐temperature anomaly. The proposed volcano‐tectonic architecture should improve the unrest scenarios in case of reactivation in this Campi Flegrei caldera sector and the monitoring strategies for the Astroni Volcano.

CBCT –THE GOLDEN GLORY OF PROSTHODONTICS: A REVIEW

Cone beam computed tomography (CBCT, also referred to as C-arm computed tomography [CT], cone beam volume CT, or at panel CT) is a medical imaging technique of X-ray CT where the X-rays are divergent,forming a cone. It provides a complete 3D view of the maxilla, mandible, teeth, and supporting structures with relatively high resolution allowing a more accurate diagnosis, treatment planning and monitoring, and analysis of outcomes than conventional 2D images, along with low radiation exposure to the patient. This article is intended to elaborate and enunciate on the various applications and benets of CBCT, in the realm of maxillofacial prosthodontics, over and beyond its obvious benets in the rehabilitation of patients with implants. A web-based search for relevant articles in this specic area of interest was also conducted.The selected articles were critically reviewed and the data acquired were systematically compiled.

The chondro-osseous junction of articular cartilage

In the synovial joints the transition between the soft articular cartilage and the subchondral bone is mediated by a layer of calcified cartilage of structural and mechanical characteristics closer to those of bone. This layer, buried in the depth of articular cartilage, is not directly accessible and is mostly visualized in histological sections of decalcified tissue, where it appears as a darker strip in contact with the subchondral bone. In this study conventional histology and scanning electron microscopy (SEM) with secondary electron imaging (SE) or backscattered electron imaging (BSE) were used to discriminate the calcified and the uncalcified cartilage in high resolution on native, untreated tissue as well as in deproteinated or demineralized tissue. This approach evidenced a high heterogeneity of the calcified layer of articular cartilage. High resolution pictures revealed that the mineralization process originates by progressive accretion and confluence of individual, small mineral clusters, in a very different way from other hard tissues such as bone, dentin and mineralized tendons. Finally, selective removal of the soft matrix by thermal treatment allowed for the first time a face-on, unrestricted 3D view of the mineralization front.

Remote Training for Medical Staff in Low-Resource Environments Using Augmented Reality.

This work aims to leverage medical augmented reality (AR) technology to counter the shortage of medical experts in low-resource environments. We present a complete and cross-platform proof-of-concept AR system that enables remote users to teach and train medical procedures without expensive medical equipment or external sensors. By seeing the 3D viewpoint and head movements of the teacher, the student can follow the teacher's actions on the real patient. Alternatively, it is possible to stream the 3D view of the patient from the student to the teacher, allowing the teacher to guide the student during the remote session. A pilot study of our system shows that it is easy to transfer detailed instructions through this remote teaching system and that the interface is easily accessible and intuitive for users. We provide a performant pipeline that synchronizes, compresses, and streams sensor data through parallel efficiency.