Three-dimensional Reconstruction System Research Articles

Anterior pelvic tilt increases hamstring strain and is a key factor to target for injury prevention and rehabilitation.

Hamstring muscle strain injury is very common in sports involving high-speed running. Hamstring muscles originate from the ischial tuberosity and thus pelvic position may influence hamstring strain during different sports movements like sprinting, but this has only been evaluated by indirect methods. This study tested the hypothesis that a change in anterior pelvic tilt causes elongation of the overall hamstring complex and disproportionately elongates proximal relative to distal muscle regions. Seven fresh-frozen specimens (full lower limb with pelvis and lumbar spine) were used for this in vitro study. Specimens were dissected to enable visualization of the hamstring muscles and then fixed into a custom-made testing bench that allowed controlled movement of the pelvis over a fixed femur and tibia. Nine markers were inserted into the hamstring muscles to allow intra- and intermuscle difference measurements. Then, six different anterior pelvic angles were used to measure the difference in hamstring muscle lengthening through a three-dimensional reconstruction system based on stereoscopic machine vision technology. An increase in anterior pelvic tilt produced a significant non-uniform increase in tissue elongation in all regions of the three hamstring muscles (semitendinosus, semimembranosus [SMB] and biceps femoris long head), which was greater in the proximal (>1 cm every 5°) compared to the distal region (≈0.4 cm every 5°). At the proximal hamstring region, SMB showed significantly greater length changes compared to conjoint tendons with nonstatistically significant elongation differences between muscles at the distal region. Considering the results of the study, the pelvis segment will likely play a fundamental role as a strain regulator of hamstring muscles. These results will have an impact on injury rehabilitation and prevention processes of hamstring injuries, as well as optimize future musculoskeletal models and avoid potential underestimation of the hamstring muscle-tendon complex lengthening during high-speed running. N/A.

Three-Dimensional Structure Reconstruction System of Nasal Cavity Based on a Short-Source Acoustic Tube

The nasal cavity three-dimensional structure reconstruction is significant for the diagnosis and treatment of nasal and nasopharynx diseases. Currently, most systems for nasal cavity three-dimensional structure reconstruction are based on a long-source acoustic tube. However, the long-source acoustic tube has the weaknesses of low portability and high cost. To address these issues, a nasal cavity three-dimensional structure reconstruction system based on a short-source acoustic tube was designed in this research. The designed system comprises the lower computer of a nasal acoustic signal acquisition device and the upper computer of nasal acoustic signal analysis software. The lower computer of a nasal acoustic signal acquisition device consists of a signal processing unit, a detection unit, a microcontroller, and a USB communication interface. It is used to collect the original acoustic signal in the nasal cavity. The upper computer of nasal acoustic signal analysis software consists of the nasal cavity acoustic signal preprocessing method and the nasal cavity three-dimensional structure hierarchical reconstruction method. The nasal cavity acoustic signal preprocessing method is used to eliminate the DC offset component and suppress the high-frequency noise. Then, the nasal cavity three-dimensional structure hierarchical reconstruction method is used to establish the relationship between the cross-sectional area of the nasal cavity and the depth of the nasal cavity. In order to verify the effectiveness of the system designed in this research, the straight tube model and the simulated nasal cavity model were selected as test subjects, and the depth–cross-sectional area was selected as the evaluation indicator of the accuracy of the nasal cavity three-dimensional structure reconstruction result. The experimental results show that the root mean squared error and the mean relative error of the depth–cross-sectional area were reduced from 0.6284 cm2 to 0.0201 cm2 and 47.6467% to 1.8248%, respectively, under the straight tube model by using the nasal cavity acoustic signal preprocessing method. The root mean squared error and the mean relative error of the depth–cross-sectional area were reduced from 4.7730 cm2 to 0.1510 cm2 and 107.8128% to 3.3096%, respectively, under the simulated nasal cavity model. Meanwhile, this system can increase the effective measurement depth of the nasal cavity from 7 cm to 13 cm based on the preprocessing method. The results demonstrated that the designed system can not only reconstruct and visualize a nasal cavity three-dimensional structure with high precision but also generate comprehensive test reports. Therefore, this system can provide a basis for further auxiliary diagnosis of the disease and facilitate doctors in explaining the physiological structure of the nasal cavity to patients.

Thoracoscopic sublobar resection for congenital bronchial atresia in adults: a report of three cases

BackgroundCongenital bronchial atresia (CBA) is a rare bronchial abnormality. Adult patients with CBA generally do not show any symptoms. Although surgical resection is the first-line treatment, the indication for the surgical intervention is controversial, especially in mildly symptomatic or asymptomatic patients. Recently, thoracoscopic surgery is the commonly preferred approach to treat this condition.Case presentationCase 1: A woman in her 20s suffered from repeating episodes of fever and cough due to left CBA with the interruption of B9 and B10. Uniportal thoracoscopic left lower lobe wedge resection was performed, following which the symptoms disappeared. Case 2: A woman in her 40s presented to the clinic with dyspnea on exertion, and the computed tomography image revealed the absence of B2. Multiportal thoracoscopic right S2 segmentectomy was performed on her, after which the symptoms of dyspnea improved. Case 3: A woman in her 40s visited the hospital with symptoms of intermittent cough, sputum, and slight fever for 7 months. The examinations identified the absence of B6a. Right S6 segmentectomy and S2 wedge resection were carried out by multiportal thoracoscopic approach. The patient is now asymptomatic.ConclusionsBased on our experiences in the three adult CBA surgery cases, the three-dimensional image reconstruction system is very useful for diagnosis and surgical decisions with regard to this disease. Even for CBA patients with subtle symptoms, early surgical treatments may be beneficial from the point of view of minimally invasive interventions, and sublobar resection will be sufficient for treatments and preservation of respiratory function.

A portable geometry-independent tomographic system for gamma-ray, a next generation of nuclear waste characterization

One of the main activities of the nuclear industry is the characterisation of radioactive waste based on the detection of gamma radiation. Large volumes of radioactive waste are classified according to their average activity, but often the radioactivity exceeds the maximum allowed by regulators in specific parts of the bulk. In addition, the detection of the radiation is currently based on static detection systems where the geometry of the bulk is fixed and well known. Furthermore, these systems are not portable and depend on the transport of waste to the places where the detection systems are located. However, there are situations where the geometry varies and where moving waste is complex. This is especially true in compromised situations.We present a new model for nuclear waste management based on a portable and geometry-independent tomographic system for three-dimensional image reconstruction for gamma radiation detection. The system relies on a combination of a gamma radiation camera and a visible camera that allows to visualise radioactivity using augmented reality and artificial computer vision techniques. This novel tomographic system has the potential to be a disruptive innovation in the nuclear industry for nuclear waste management.

Evaluation of total tumor volume reduction ratio in initially unresectable colorectal liver metastases after first-line systemic treatment

PurposeTotal tumor volume (TTV) may play an essential role in the estimation of tumor burden. This study is aimed to investigate the clinical value of the reduction ratio of TTV as a valuable indicator of clinical outcomes in patients with colorectal liver metastases (CRLM). MethodsA total of 240 initially unresectable CRLM patients who underwent first-line systemic treatment were enrolled in this study. TTV at baseline and at the end of first-line treatment were assessed using a three-dimensional reconstruction system according to CT or MRI images. Survival was evaluated using Kaplan-Meier analysis and compared using Cox proportional hazard ratios (HR). ResultsA total of 212 (88.3%) patients achieved tumor regression with a median reduction ratio of TTV of 86.0%. An increasing reduction ratio of TTV was associated with a gradually ascending successful conversion outcome. Patients with a reduction ratio >86.0% had better survival than those with a reduction ratio 0–86.0% or <0 (5-year overall survival (OS) rates, 64.4% vs. 44.9% vs. 23.5%, P < 0.001; 5-year progression-free survival (PFS) rates, 36.3% vs. 28.2% vs. 6.5%, P < 0.001). Multivariate analysis indicated that the reduction ratio of TTV ≤ 86.0% (OR [95%CI]: 4.956 [2.654–9.253], P < 0.001) was an independent factor for conversion failure outcome. Cox analyses revealed that the reduction ratio of TTV ≤ 86.0% was an independent factor for both unfavorable OS (HR [95%CI]: 2.216 [1.332–3.688], P = 0.002) and PFS (HR [95%CI]: 2.023 [1.376–2.974], P < 0.001). ConclusionsThe reduction ratio of TTV was an effective indicator for conversion outcome and long-term prognosis in patients with initially unresectable CRLM after first-line systemic treatment.

Three-dimensional reconstruction system in pulmonary broncho vascular surgery using AI.

Three-dimensional reconstruction system in pulmonary broncho vascular surgery using AI.

Accuracy and efficiency of an artificial intelligence-based pulmonary broncho-vascular three-dimensional reconstruction system supporting thoracic surgery: Retrospective and prospective validation study.

Anthropomorphic phantoms are used in surgical planning and intervention. Ideal accuracy and high efficiency are prerequisites for its clinical application. We aimed to develop a fully automated artificial intelligence-based three-dimensional (3D) reconstruction system (AI system) to assist thoracic surgery and to determine its accuracy, efficiency, and safety for clinical use. This AI system was developed based on a 3D convolutional neural network (CNN) and optimized by gradient descent after training with 500 cases, achieving a Dice coefficient of 89.2%. Accuracy was verified by comparing virtual structures predicted by the AI system with anatomical structures of patients in retrospective (n=113) and prospective cohorts (n=139) who underwent lobectomy or segmentectomy at the Peking University Cancer Hospital. Operation time and blood loss were compared between the retrospective cohort (without AI assistance) and prospective cohort (with AI assistance) for safety evaluation. The time consumption for reconstruction and the quality score were compared between the AI system and manual reconstruction software (Mimics®) for efficiency validation. This study was registered at https://www.chictr.org.cn as ChiCTR2100050985. The AI system reconstructed 13,608 pulmonary segmental branches from retrospective and prospective cohorts, and 1573 branches of interest corresponding to phantoms were detectable during the operation for verification, achieving 100% and 97% accuracy for segmental bronchi, 97.2% and 99.1% for segmental arteries, and 93.2% and 98.8% for segmental veins, respectively. With the assistance of the AI system, the operation time was shortened by 24.5min for lobectomy (p<0.001) and 20min for segmentectomy (p=0.007). Compared to Mimics®, the AI system reduced the model reconstruction time by 14.2min (p<0.001), and it also outperformed Mimics® in model quality scores (p<0.001). The AI system can accurately predict thoracic anatomical structures with higher efficiency than manual reconstruction software. Constant optimization and larger population validation are required. This study was funded by the Beijing Natural Science Foundation (No. L222020) and other sources.

The analysis of the structural parameter influences on measurement errors in a binocular 3D reconstruction system: a portable 3D system.

This study used an analytical model to investigate the factors that affect the reconstruction accuracy composed of the baseline length, lens focal length, the angle between the optical axis and baseline, and the field of the view angle. Firstly, the theoretical expressions of the above factors and measurement errors are derived based on the binocular three-dimensional reconstruction model. Then, the structural parameters' impact on the error propagation coefficient is analyzed and simulated using MATLAB software. The results show that structural parameters significantly impact the error propagation coefficient, and the reasonable range of structural parameters is pointed out. When the angle between the optical axis of the binocular camera and the baseline is between 30° and 55°, the ratio of the baseline length to the focal length can be reasonably reduced. In addition, using the field angle of the view that does not exceed 20° could reduce the error propagation coefficient. While the angle between the binocular optical axis and the baseline is between 40° and 50°, the reconstruction result has the highest accuracy, changing the angle out of this range will lead to an increase in the reconstruction error. The angle between the binocular optical axis and the baseline changes 30° through 60° leads to the error propagation coefficient being in a lower range. Finally, experimental verification and simulation results show that selecting reasonable structural parameters could significantly reduce measurement errors. This study proposes a model that constructs a binocular three-dimensional reconstruction system with high precision. A portable three-dimensional reconstruction system is built in the article.

Three-Dimensional Relief Reconstruction System Based on Laser Line Scanning

Three-Dimensional Relief Reconstruction System Based on Laser Line Scanning

3D Reconstruction of Traditional Handicrafts Based on Binocular Vision

As an indispensable and essential material part of China's traditional culture, traditional handicrafts have played a more important role in modern life. It is not only the crystallization of the wisdom of the Chinese people of all nationalities but also an excellent platform to display China's long-standing culture. However, the protection and reconstruction of traditional handicrafts are relatively lagging. To realize the reconstruction of traditional handicrafts, this paper proposes an improved AD-Census stereo matching algorithm of a binocular measurement system for object positioning and three-dimensional reconstruction. Methods based on the principle of binocular vision measurement include firstly, histogram equalization, adaptive threshold Canny edge extraction, and expansion are used for image preprocessing; Secondly, the calibration method is used to complete camera calibration, remove camera distortion through stereo correction, and improve the AD-Census stereo matching algorithm based on gradient division of weak texture and edge area. Finally, the parallax map generated by the improved algorithm is used to realize three-dimensional reconstruction. The experimental results show that this method can control the error standard deviation within 0.5 mm, can realize the reconstruction of traditional handicrafts, have high accuracy, and can be widely used in practice.

3D Virtual Modeling Realizations of Building Construction Scenes via Deep Learning Technique.

The architectural drawings of traditional building constructions generally require some design knowledge of the architectural plan to be understood. With the continuous development of the construction industry, the use of three-dimensional (3D) virtual models of buildings is quickly increased. Using three-dimensional models can give people a more convenient and intuitive understanding of the model of the building, and it is necessary for the painter to manually draw the 3D model. By analyzing the common design rules of architectural drawing, this project designed and realized a building three-dimensional reconstruction system that can automatically generate a stereogram (3 ds format) from a building plan (dxf format). The system extracts the building information in the dxf plan and generates a three-dimensional model (3 ds format) after identification and analysis. Three-dimensional reconstruction of architectural drawings is an important application of computer graphics in the field of architecture. The technology is based on computer vision and pattern recognition, supported by artificial intelligence, three-dimensional reconstruction, and other aspects of computer technology and engineering domain knowledge. It specializes in processing architectural engineering drawings with rich semantic information and various description forms to automatically carry out architectural drawing layouts. The high-level information with domain meanings such as the geometry and semantics/functions of graphics of the buildings can be analyzed for forming a complete and independent research system. As a new field of computer technology, the three-dimensional reconstruction drawings are appropriate for demonstrating the characteristics of architectural constructions.

Smart three-dimensional processing of unconstrained cave scans using small unmanned aerial systems and red, green, and blue-depth cameras

This article focuses on a novel three-dimensional reconstruction system that maps large archeological caves using data collected by a small unmanned aircraft system with red, green, and blue-depth cameras. Cave sites often contain the best-preserved material in the archeological record. Yet few sites are fully mapped. Large caves environment usually contains complex geometric structures and objects, which must be scanned with long overlapped camera trajectories for better coverage. Due to the error in camera tracking of such scanning, reconstruction results often contain flaws and mismatches. To solve this problem, we propose a framework for surface loop closure, where loops are detected with a compute unified device architecture accelerated point cloud registration algorithm. After a loop is detected, a novel surface loop filtering method is proposed for robust loop optimization. This loop filtering method is robust to different scan patterns and can cope with tracking failure recovery so that there is more flexibility for unmanned aerial vehicles to fly and record data. We run experiments on public data sets and our cave data set for analysis and robustness tests. Experiments show that our system produces improved results on baseline methods.

Three-dimensional reconstruction and filtration behavior analysis system for nanofiber membrane

Three-dimensional reconstruction and filtration behavior analysis system for nanofiber membrane

Accuracy and Efficiency of a Novel Artificial Intelligence-Based Pulmonary Broncho-Vascular Three-Dimensional Reconstruction System Supporting Thoracic Surgery: Retrospective and Prospective Validation Study

Accuracy and Efficiency of a Novel Artificial Intelligence-Based Pulmonary Broncho-Vascular Three-Dimensional Reconstruction System Supporting Thoracic Surgery: Retrospective and Prospective Validation Study

A Calibration Method for a Self-Rotating, Linear-Structured-Light Scanning, Three-Dimensional Reconstruction System Based on Plane Constraints

This paper proposes a calibration method for a self-rotating, linear-structured-light (LSL) scanning, three-dimensional reconstruction system based on plane constraints. The point cloud of plane target collected by the self-rotating, LSL scanning, 3D reconstruction system should be constrained to the basic principle of the plane equation; it can quickly and accurately calibrate the position parameters between the coordinate system of the LSL module and the coordinate system of the self-rotating, LSL scanning, 3D reconstruction system. Additionally, the transformation equation could be established with the calibrated optimal position parameters. This paper obtains the above-mentioned position parameters through experiments and uses the calibrated self-rotating, LSL scanning, 3D reconstruction system to perform three-dimensional scanning and reconstruction of the test piece. The experimental results show that the calibration method can effectively improve the measurement accuracy of the system.

Plane Visual Communication Design of User Experience Effect Based on Computer Simulation

With the development and popularization of computer simulation technology, its application in all walks of life has become more and more extensive, and it has also effectively promoted the development of all walks of life. This article analyzes the elements of flat visual communication design, and it decomposes the multi-level structure of user experience effects in flat visual communication design. In addition, the design of plane visual communication requires the aid of a three-dimensional reconstruction system, so this paper also studies the hardware design and software design of the three-dimensional image virtual reconstruction system.

A Three-Dimensional Scanning System for Digital Archiving and Quantitative Evaluation of Arabidopsis Plant Architectures.

A plant’s architecture contributes to its ability to acquire resources and reduce mechanical load. Arabidopsis thaliana is the most common model plant in molecular biology, and there are several mutants and transgenic lines with modified plant architecture regulation, such as lazy1 mutants, which have reversed angles of lateral branches. Although some phenotyping methods have been used in larger agricultural plants, limited suitable methods are available for three-dimensional reconstruction of Arabidopsis, which is smaller and has more uniform surface textures and structures. An inexpensive, easily adopted three-dimensional reconstruction system that can be used for Arabidopsis is needed so that researchers can view and quantify morphological changes over time. We developed a three-dimensional reconstruction system for A. thaliana using the visual volume intersection method, which uses a fixed camera to capture plant images from multiple directions while the plant slowly rotates. We then developed a script to autogenerate stack images from the obtained input movie and visualized the plant architecture by rendering the output stack image using the general bioimage analysis software. We successfully three-dimensionally and time-sequentially scanned wild-type and lazy1 mutant A. thaliana plants and measured the angles of the lateral branches. This non-contact, non-destructive method requires no specialized equipment and is space efficient, inexpensive and easily adopted by Arabidopsis researchers. Consequently, this system will promote three- and four-dimensional phenotyping of this model plant, and it can be used in combination with molecular genetics to further elucidate the molecular mechanisms that regulate Arabidopsis architecture.

One-Shot M-Array Pattern Based on Coded Structured Light for Three-Dimensional Object Reconstruction

Pattern encoding and decoding are two challenging problems in a three-dimensional (3D) reconstruction system using coded structured light (CSL). In this paper, a one-shot pattern is designed as an M-array with eight embedded geometric shapes, in which each 2 × 2 subwindow appears only once. A robust pattern decoding method for reconstructing objects from a one-shot pattern is then proposed. The decoding approach relies on the robust pattern element tracking algorithm (PETA) and generic features of pattern elements to segment and cluster the projected structured light pattern from a single captured image. A deep convolution neural network (DCNN) and chain sequence features are used to accurately classify pattern elements and key points (KPs), respectively. Meanwhile, a training dataset is established, which contains many pattern elements with various blur levels and distortions. Experimental results show that the proposed approach can be used to reconstruct 3D objects.

Georeferencing kinematic modeling and error correction of terrestrial laser scanner for 3D scene reconstruction

Georeferencing means to transform the point cloud data collected by the terrestrial laser scanner (TLS) into a global coordinate system for three-dimensional (3D) scene reconstruction. However, the current georeferencing methods are mainly applicable for the TLS operating in the static mode; when the TLS is moving (i.e., in the kinematic working mode) during the 3D scene reconstruction, severe georeferencing error will be generated due to the kinematic measurement noise and geometric falsification offsets. To bridge this research gap, a new method based on the kinemics state constraints converted measuring Kalman Filter (KSC-CMKF) and the Levenberg Marquardt Wavelet neural network (LM-WNN) is proposed to correct the TLS georeferencing error in the kinematic operating mode (i.e., TLS kinematic georeferencing error). This new method can automatically correct the georeferencing error and simultaneously reduce the TLS systematic bias to save time and cost for the kinematic georeferencing. In order to achieve the georeferencing error correction, two kinematic models are established to respectively address the straight-line movement and turn movement scenarios. Then, the LM-WNN algorithm is used to estimate the uncertain propagation of the TLS kinemics error model to optimize the kinematic parameters. Subsequently, the KSC-CMKF algorithm is applied to correcting the coordinate transformation error between the TLS spherical coordinate and the global Cartesian coordinate. Lastly, the pre-survey signalized spherical targets are adopted as the ground control points to evaluate the performance of the TLS kinematic georeferencing. Experimental results demonstrate that the overall accuracy of the proposed TLS kinematic georeferencing method for the 3D scene reconstruction is significantly improved and is superior to that of two existing popular methods.

Research on the Accuracy and Speed of Three-Dimensional Reconstruction of Liver Surface Based on Binocular Structured Light

In view of the problem that the doctor cannot quickly obtain the three-dimensional information of the liver surface during the traditional open resection of liver tumor without radiation, a new three-dimensional reconstruction system of liver surface based on binocular structured light is proposed in this paper to obtain three-dimensional information of liver surface rapidly. The hardware construction and software module design of the three-dimensional reconstruction system of the liver surface are carried out. The multi-frequency heterodyne method is proposed to solve the problem of the lack of three-dimensional reconstruction of the liver surface. A GPU-CPU collaborative acceleration method is proposed to speed up the three-dimensional reconstruction of intraoperative liver surface. On this basis, a human respiratory platform is built to simulate the effect of human respiration on three-dimensional reconstruction of the liver surface in a real surgical environment. The accuracy and speed of the system are verified by the liver experiments: The errors of three-dimensional reconstruction of liver surface at expiratory peak and inspiratory peak are 0.78 ± 0.18mm and 0.92 ± 0.21 mm, respectively. The average time required for three-dimensional reconstruction of liver surface based on GPU-CPU collaborative calculation is 3.93s. The speed of three-dimensional reconstruction of liver surface based on GPU-CPU collaborative calculation is 52% faster than that of three-dimensional reconstruction of liver surface based on CPU. It can be seen that the system has high accuracy and fast speed, which can meet the basic needs of the doctor in surgery.