Scanning Technology Research Articles

The potential of photon-counting CT for the improved precision of lung nodule radiomics

Abstract Lung nodule appearance may provide prognostic information, as the presence of spiculation increases the suspicion of a nodule being cancerous. Spiculations can be quantified using morphological radiomics features extracted from CT images. Radiomics features can be affected by the acquisition parameters and scanner technologies; thus, it is essential to identify imaging conditions that provide reliable measurements, particularly for emerging technologies like photon-counting CT. This study aimed to systematically quantify the effect of imaging parameters on the radiomics measurements using a virtual imaging trial (VIT) platform, and further verify the findings with human clinical data. The VIT utilized nine virtual patients, each with three 6-mm nodules of varying spiculations. The virtual patients were run through a validated CT simulator (DukeSim) to acquire images at three dose levels (CTDIvol = 2.85, 5.69, and 11.38 mGy) with a clinical energy-integrating CT and a photon-counting CT. The acquired projection images were reconstructed using multiple slice thicknesses, kernels, and matrix sizes. The reconstructed images were processed to extract morphological features using three segmentation methods. The features were clustered into three broad type categories. Features extracted from the acquired CT images were compared to their corresponding ground truth values, across all imaging conditions. Among all imaging conditions, slice thickness had the greatest effect on the radiomics measurements. When the thickest slices were used, the coefficient of variation increased by [1.19—9.66%] in the EICT images, and [3.94—24.43%] in the PCCT images. For both scanners, varying the kernel sharpness and dose affected the radiomics measurements insignificantly, while pixel size and segmentation method were observed to have stronger effects. Under varying imaging conditions, the trends and magnitude of radiomics features measurements were coherent with virtual trial results. The findings stress the importance of choosing optimal reconstruction settings for radiomics extraction to achieve precise feature quantifications.

The Temporal and Spatial Evolution of Flow Heterogeneity During Water Flooding for an Artificial Core Plate Model

In the process of reservoir water flooding development, the characteristics of underground seepage field have changed, resulting in increasingly complex oil–water distribution. The original understanding of reservoir physical property parameters based on the initial stage of development is insufficient to guide reservoir development efforts in the extra-high water cut stage. To deeply investigate the spatio-temporal evolution of heterogeneity in the internal seepage field of layered reservoirs during water flooding development, water–oil displacement experimental simulations were conducted based on layered, normally graded models. By combining CT scanning technology and two-phase seepage theory, the variation patterns of heterogeneity in the seepage field of medium-to-high permeability, normally graded reservoirs were analyzed. The results indicate that the effectiveness of water flooding development is doubly constrained by differences in oil–water seepage capacities and the heterogeneity of the seepage field. During the development process, both the reservoir’s flow capacity and the heterogeneity of the seepage field are in a state of continuous change. Influenced by the extra resistance brought about by multiphase flow, the reservoir’s flow capacity drops to 41.6% of the absolute permeability in the extra-high water cut stage. Based on differences in the variation amplitudes of oil–water-phase permeabilities, changes in the heterogeneity of the internal seepage field of the reservoir can be broadly divided into periods of drastic change and relative stability. During the drastic change stage, the fluctuation amplitude of the water-phase permeability variation coefficient is 114.5 times that of the relative stable phase, while the fluctuation amplitude of the oil-phase permeability variation coefficient is 5.2 times that of the stable stage. This study reveals the dynamic changes in reservoir seepage characteristics during the water injection process, providing guidance for water injection development in layered reservoirs.

Real-Time Monitoring System for Local Subsidence Deformation in GIS Based on 3D Laser Scanning Technology

Real-Time Monitoring System for Local Subsidence Deformation in GIS Based on 3D Laser Scanning Technology

Study on the mechanical properties and failure mechanism of a multi-lithologic layered rock mass.

The mechanical properties of multi-lithologic reservoir rock masses are complex, and the failure mechanism is not clear. This research belongs to the field of oil and gas exploration and development. Brazilian splitting, and digital image correlation (DIC) tests were performed to study the mechanical properties and failure mechanism of assemblages containing sandstone, shale, and limestone. In the Brazilian splitting test, the tensile strength of the rock mass first increased and then decreased with an increasing angle. As the interface angle increased, The morphology of the splits is also changing. In the DIC test, according to the deformation characteristics at different angles, the Brazilian splitting test process was summarized into three stages: interface deformation, elastoplastic, and failure, the interface has a great influence on the fracture propagation, and the fracture tends to expand along the interface. Interface characteristics were studied based on 3D scanning technology and fractal method, with an increase in the angle, the fractal dimension D showed first decreased, then increased, and further decreased, which was identical to the variation trend of the maximum load in the Brazilian splitting test and the maximum principal strain in the DIC test with the angle. This study provides reference for predicting fracture propagation trend in field hydraulic fracturing work.

Features of Terrestrial Laser 3D Scanning Technology for Pavement Condition Assessment

Abstract. Problem. Traditional methods of road condition monitoring have limitations in terms of data accuracy and completeness, particularly in the detection of surface defects. There is a need for methods that provide accurate, rapid data collection to support effective maintenance and repair planning. Goal. The goal of this study is to develop and optimise a methodology for terrestrial 3D laser scanning and to provide practical recommendations for its application in road surface monitoring. Methodology. The proposed methodology examines the effectiveness of terrestrial laser scanning on road segments, addressing parameters such as optimal station count, placement and scanning mode to ensure accurate and comprehensive data collection. The Trimble TX6 scanner is used as an example, with specifications including a range of up to 120 metres, 2 mm accuracy and an adjustable scanning speed of up to 500,000 points per second. Results. The research identifies optimal setups for different road segments, covering short (~100–150 m) and long (up to 1000 m) sections, as well as complex road infrastructure such as multi-level interchanges. The results demonstrate the ability of the 3D scanning method to detect various linear and areal pavement defects. Originality. This study advances the field by developing specific recommendations for station positioning and scanning protocols, addressing blind spots, and ensuring data integrity for 3D modelling. Practical value. The application of this technology supports detailed analysis of pavement condition, significantly increasing the efficiency of data processing and improving repair planning and material estimation. The results are beneficial for transport infrastructure management, enabling more reliable monitoring and maintenance practices

Revolutionizing art exhibitions: Photogrammetry's role in virtual reality experiences

The COVID-19 pandemic significantly impacted many aspects of human life, including the way we work, travel, and even our art-viewing habits. In the past, art exhibitions were the primary channel through which art lovers could view, experience, and purchase artwork. However, the pandemic brought the art industry to a sudden halt as people are unable to visit physical exhibitions. Even after the pandemic has passed, what will happen if a similar outbreak occurs? Recent advances in photogrammetry, 3D scanning, and virtual reality technology enable the creation of an immersive and realistic digital environment. The integration of the two technologies could be a revolutionary approach to art presentation. In this mixed-method study, the researchers used a photogrammetry scanning technique to scan sculptures of His Majesty King Bhumibol Adulyadej and turn them into a virtual reality exhibition. We invited three experts in art, design, and technology to share their perspectives on the exhibition. We asked forty-five participants to evaluate the exhibition's ease of use, level of immersion, and satisfaction. The study reveals expert and participant feedback on a virtual reality exhibition. The visual art expert praised the virtual reality experience for offering new opportunities and remarkable immersion, though it lacked tactile elements compared to physical galleries. The design expert lauded the intuitive navigation and impressive spatial design, which enhanced immersion. The technology expert noted that while a photogrammetry-based virtual reality experience offers unprecedented immersion, the quality varies based on hardware and technical factors. Participants found the virtual reality exhibition largely positive, with 86.7% rating it as easy or very easy to use. More than 91% felt the exhibition was immersive, and 100% were satisfied, with 62.2% expressing extreme satisfaction. These results highlight the strong potential of virtual reality exhibitions.

Quantification of the pulmonary vasculature in mice under chronic hypoxia with contrast-free pulmonary angiography in vivo imaging.

Innovative advancements in preclinical imaging have led to the development of cone-beam computed tomography (CBCT) combined with contrast-free pulmonary angiography (CFPA), a novel lung scanning technology capable of assessing lung function and pulmonary vascular morphology. This cutting-edge approach integrates CBCT to provide detailed quantification of the pulmonary vascular tree. The application of this technique to image and quantify changes in the pulmonary vascular tree of mice exposed to chronic hypoxia has not been investigated. In this study, we investigated the feasibility of utilizing CFPA for imaging changes in the murine lung vascular bed under chronic hypoxia and assessed whether vascular metrics correlate with hematologic parameters and/or right ventricular pressure and mass. Our results revealed a significant increase in hemoglobin and total pulmonary vascular blood volume, as well as total pulmonary vessel length following exposure to chronic hypoxia. The pulmonary vascular blood volume and total vessel length strongly correlated with hemoglobin. There was also an increase in pulmonary arterial pressure and right ventricular mass under hypoxia that was linked to the hematological response and the changes in the pulmonary vascular bed. These findings highlight the application of preclinical CBCT and CFPA imaging as a valuable tool for visual and quantitative analysis of the pulmonary vasculature in preclinical models of chronic hypoxia and its potential use in investigating other pulmonary vasculopathies.NEW & NOTEWORTHY Cone-beam computed tomography (CBCT) combined with contrast-free pulmonary angiography (CFPA) is a novel lung scanning technology capable of assessing pulmonary vascular morphology in vivo in murine models.

Airborne LiDAR Applications at the Medieval Site of Castel Fenuculus in the Lower Valley of the Calore River (Benevento, Southern Italy)

This paper explores the application of Airborne Laser Scanning (ALS) technology in the investigation of the medieval Norman site of Castel Fenuculus, in the lower Calore Valley, Southern Italy. This research aims to assess the actual potential of the ALS dataset provided by the Italian Ministry of the Environment (MATTM) for the detection and visibility of archaeological features in a difficult environment characterised by dense vegetation and morphologically complex terrain. The study focuses on improving the detection and interpretation of archaeological features through a systematic approach that includes the acquisition of ALS point clouds, the implementation of classification algorithms, and the removal of vegetation layers to reveal the underlying terrain and ruined structures. Furthermore, the aim was to test different classification and filtering techniques to identify the best one to use in complex contexts, with the intention of providing a comprehensive and replicable methodological framework. Finally, the Digital Elevation Model (DTM), and various LiDAR-derived models (LDMs), were generated to visualise and highlight topographical features potentially related to archaeological remains. The results obtained demonstrate the significant potential of LiDAR in identifying and documenting archaeological features in densely vegetated and wooded landscapes.

Study on the Microstructure and Permeability Characteristics of Tailings Based on CT Scanning Technology

The permeability characteristics of tailings directly affect the position of the infiltration line of the tailings dam, which is the most critical factor affecting tailings dam failures. In order to fully analyze the essence of its permeability characteristics, computed tomography (CT) technology is used to analyze the structure of different types of tailings from a microscopic perspective and carry out microscopic seepage simulation. The results showed the following findings: (1) The porosity of viscous tailings ranges from 25 to 35%, the distribution of surface porosity along the height is relatively uniform, and the distribution is shown as having a certain discrete nature with the increase in particle size. (2) Compared with silty and sandy tailings, the surface of viscous tailings is smoother and more round, and the shape factor can reach 0.95; (3) The data gap between the simulation and the measurements by CT scanning technology is less than 10%, and the estimation of the permeability characteristics is feasible, with good applicability in the simulation of tailings seepage. (4) In the microscopic pore throat structure, the permeability characteristics of the tailings are more affected by the radius of the throat than the pore radius, and the exponential function relationship between the permeability coefficient and the porosity satisfies a high correlation. In this paper, the relationship between the microstructure and permeability characteristics of tailings is analyzed by CT technology; the permeability is simulated and calculated, and a permeability coefficient prediction model for tailings is proposed in combination with the experiment, which can provide a new idea and method for the study of the permeability characteristics of tailings.

水稻籽粒堆积特性离散元法模拟研究

Accurately determining the angle of repose for irregular and dispersed agricultural grain materials requires a simulation model that effectively represents the actual grain shapes and utilizes numerical methods to analyze their stacking behavior. This study focuses on "Yongyou 15" rice grains, employing 3D raster scanning technology to obtain precise contour data. Through a reverse modeling process, a detailed 3D geometric model of the grains was developed, resulting in a discrete element model comprising 618 grains of varying diameters, created using granular polymer theory. Discrete element analysis software (EDEM) was integrated with MATLAB image processing to simulate the falling and stacking process of the rice grains within a stainless steel bottomless cylindrical tube. The contour of the grain heap was analyzed using linear fitting, followed by a micro-mechanical investigation of the grain heap structure. The analysis indicated that the pressure depression within the heap is caused by the oblique transmission of contact forces. The simulated angle of repose under experimental conditions was 31.29°±0.41°, differing by only 0.81% from the actual measured angle of 31.04°±0.21° obtained through physical stacking experiments. These results demonstrate that combining numerical simulations with image feature extraction is a reliable and efficient method for assessing the stacking properties of agricultural materials.

The Influencing Factors of Breast Morphological Changes After Dual-Plane Augmentation with Smooth Round Implans: A Correlational Study.

Breast morphology is the primary objective indicator for evaluating the outcome of augmentation surgery. Studies have indicated that breast morphology undergoes certain changes during the early postoperative period, which may result in a discrepancy between postoperative outcomes and preoperative design. This study utilized three-dimensional scanning technology and statistical methods to analyze the influencing factors of breast morphology changes, aiming to provide reference for implant selection and preoperative surgical planning. The study included patients who underwent endoscopic-assisted transaxillary dual-plane augmentation from July 2020 to June 2022. Anthropometry and three-dimensional scanning were performed on the enrolled patients, and the change values of postoperative breast morphological parameters were calculated. Spearman rank correlation tests were performed to assess the correlation between these changes and implant parameters as well as anthropometric measurements. Factors with high correlation were selected, and multivariate linear regression analysis was conducted. A total of 30 patients (60 breasts) were enrolled. The average downward displacement of the inframammary fold was 0.4 ± 0.3 cm, and the average outward displacement of the medial breast border was 0.2 ± 0.1 cm, both highly positively correlated with implant volume. The length of nipple-medial breast border increased by 0.5 ± 0.3 cm, highly positively correlated with the stretchability of the medial pole. The length of the nipple-to-inframammary fold increased by 0.6 ± 0.3 cm, highly positively correlated with implant volume and stretchability of the lower pole. Nipple displacement was 0.3 ± 0.2 cm outward, highly positively correlated with the stretchability of the medial pole. Nipple elevation was 0.2 ± 0.2 cm, highly positively correlated with implant volume and stretchability of the lower pole. Breast projection decreased by 0.4 ± 0.2 cm, highly positively correlated with preoperative breast projection. The average reduction in breast volume was 25.6 ± 15.7 cc, with the reduction value highly positively correlated with preoperative breast volume. After smooth round implant augmentation mammoplasty, the breasts experienced slight downward and outward displacement, with the main influencing factor being the implant volume. Nipple displacement outward and upward, as well as lateral displacement, was primarily influenced by the stretchability of the medial pole. Upward displacement was mainly influenced by implant volume and the stretchability of the lower pole. The increase in length of the nipple-to-inframammary fold skin was most significantly influenced by implant volume and the stretchability of the lower pole. Breast convexity and volume gradually decreased, with preoperative breast size having the most significant impact on these changes. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Improvement of mathematical methods for ensuring security based on real-time video sequence analysis

Purpose of research. Currently, mathematical methods of video sequence analysis represent a structured set of approaches to image recognition based on the difference in the glow of different image areas. Many of these values are described using mathematical dependencies, however, existing approaches work only for standard images obtained during video data processing. The purpose of this study is to develop a new approach to analyzing images obtained, including those using terahertz radiation, which has specific characteristics, both physical and mathematical.Methods. The following theoretical and empirical scientific methods were used in this study. Analysis (the analysis of the currently known mathematical methods of image processing in order to recognize images is carried out). Synthesis (a fundamentally new approach to security systems is proposed, which is a single system consisting of separate interconnected subsystems). Modeling (an information model of a security system based on ACS has been developed using a system for analyzing and recognizing potentially dangerous objects based on a real-time video stream).Mathematization (the image analysis system is described in the language of mathematical laws and formulas).Results. As a result of the research based on the analysis of modern materials, the concept of a security system based on real-time video sequence analysis with the use of advanced object scanning technologies is proposed in the future. As the main innovation, an improved Viola-Jones image analysis method is proposed using an additional set characterizing the feature space of objects in the terahertz radiation range.Conclusion. The use of high-frequency scanning technologies with intelligent object image recognition systems in real time will significantly reduce the risks of intruders entering protected facilities, as well as increase the safety of citizens with relatively low costs for the development and implementation of upgraded security systems.

Automatic Wood Species Classification and Pith Detection in Log CT Images

This article focuses on the need for digitalization in the forestry and timber sector using information from CT scans of logs. The National Forest Centre (Slovak Republic) operates a unique 3D CT scanner for wooden logs at the Stráž Biotechnology Park. This real-time scanner generates a 3D model of a log, displaying the wood’s internal features/defects. To optimize log-cutting plans effectively, it is necessary to automatically detect and classify these features and defects in real time, leveraging computer vision principles. Artificial intelligence, specifically neural networks, addresses this need by enabling solutions for tasks of this nature. Building a highly efficient neural network for detecting wood features and defects requires creating a database of log scans and training the network on these data. This is a time-intensive process, as it involves manually marking internal features and defects on hundreds of CT scans of various wood types. A functional neural network for detecting internal wood defects represents a significant advancement in sector digitalization, paving the way for further automation and robotization in wood processing. For the forestry sector to remain competitive, efficiently process raw materials, and improve product quality, the effective application of CT scanning technology is essential. This technological innovation aligns the sector more closely with leaders in other fields, such as the automotive, engineering, and metalworking industries.

Experimental Investigation on Sediment Erosion and Diffusion Characteristics During Coandă-Effect-Based Nodule Collection

Abstract Small-scale experiments were designed and conducted to investigate the sediment erosion and diffusion characteristics during Coandă-effect-based polymetallic nodule collection under a viscous sediment bed. A protocol for preparing artificial sediments was devised, and 3D scanning technology coupled with turbidimetry techniques was used to quantify the impacts of collector jet velocity v and bottom clearance h on sediment erosion and diffusion. The findings reveal that an increase in v and a decrease in h leads to an increase in the level of disturbance, with a linear trend for some of the indicators, but there are also areas of insensitivity to change. Spatially, sediment particles show a clear tendency of localized aggregation, while temporally, sediment turbidity currents show a trend of short-term fluctuations and long-term stable changes. As a result, the traditional sediment plume monitoring system has been refined, culminating in the proposal of a new monitoring model that optimally balances efficiency and economy.

Comparative finite element analysis between three surgical techniques for the treatment of type VI schatzker tibial plateau fractures

Introduction. Open reduction internal fixation (ORIF) and external fixation are traditional surgical techniques for treating type VI Schatzker tibial plateau fractures. A newly developed technique integrates the intramedullary tibial nail with condylar bolts. This finite element study investigated the mechanical response of three surgical techniques for fixing type VI Schatzker tibial plateau fractures. We compared the intramedullary nail-bolt (IMNB) technique with the single lateral locking plate (SLLP) and dual plating (DP) techniques.Materials and Methods. A 4th generation Sawbone model of a left tibia with a Type VI tibial plateau fracture was scanned using computed tomography and reconstructed into a 3D model. The plates were digitally reconstructed using 3D scanning technology, while the screws, condylar bolt, and nail were replicated using commercial computer-aided design software. An application engineer guided by a surgeon, virtually positioned the bone-implant construct for the three surgical techniques to align with physical constructs from a previousin-vitrobiomechanical study. A commercial finite element analysis software was used for the computer simulation, with the tibial plateau subjected to uniaxial loads at 500, 1000, and 1500 Newton while the distal tip of the tibia remained fixed. Measurements of vertical subsidence, horizontal diastasis, and passive construct stiffness were recorded and compared to those of the previousin-vitrobiomechanical experiment.Results.DP had the highest stiffness, followed by IMNB and SLLP techniques. DP also resulted in smaller values for measured subsidence and diastasis compared to SLLP and IMNB. The simulation results aligned with those of thein-vitrobiomechanical study.Conclusions.The simulation results may further support the initial suggestion of thein-vitrobiomechanical study that the IMNB technique is a biomechanically suitable method for fixing Type VI Schatzker injuries.

Optical aberration effects on beam quality in microlens array scanning systems

Microlens array scanning (MLAS) has emerged as a promising semi-solid micromechanical beam scanning technology, which has significant potential in fields such as LIDAR and free-space optical communication. Beam quality is a crucial performance index in MLAS, which directly affects the overall performance of the system. To better evaluate and optimize the performance of the MLAS system, we investigate the effect of aberrations on this critical parameter of MLAS beam quality. This paper commences by constructing a model of the Kepler-structured MLAS system affected by aberrations based on the wave aberration theory. A detailed examination is conducted on the influence of both uniform and non-uniform wave aberrations within the MLAS on the beam quality. This paper investigates the effects of defocus, astigmatism, coma, and spherical aberration on the far-field intensity distribution of the MLAS system by using the Zernike aberration decomposition technique. Employing the Strehl ratio (SR) and power-in-the-bucket (PIB) as quantitative evaluation indices of beam quality, this study calculates the aberration-induced alterations in far-field focusing ability and energy concentration. The findings of this study provide valuable insights for the design optimization, manufacturing, and assembly testing of MLAS technologies.

Automated Characterization of Abdominal MRI Exams Using Deep Learning.

Advances in magnetic resonance imaging (MRI) have revolutionized disease detection and treatment planning. However, as the volume and complexity of MRI data grow with increasing heterogeneity between institutions in imaging protocol, scanner technology, and data labeling, there is a need for a standardized methodology to efficiently identify, characterize, and label MRI sequences. Such a methodology is crucial for advancing research efforts that incorporate MRI data from diverse populations to develop robust machine learning models. This research utilizes convolutional neural networks (CNNs) to automatically classify sequence, orientation, and contrast, specifically tailored for abdominal MRI. Three distinct CNN models with similar backbone architectures were trained to classify single image slices into one of 12 sequences, 4 orientations, and 2 contrast classes. Results derived from this method demonstrate high levels of performance for the three specialized CNN models, with model accuracies for sequence, orientation, and contrast of 96.9%, 97.4%, and 97.3%, respectively.

Using Digital Methods to Work on an Existing Sculptural Object or One in The Process of Physical Fabrication

The report examines key aspects of using digital methods in working on sculptural objects, both existing and in progress. An analysis of current trends and the impact of technological advances in sculpture is presented, with a focus on 3D scanning and virtual modelling Digital methods and tools and software platforms and hardware technologies for scanning, modelling and virtual creation are explored. Through a review of real-world examples and research projects, the possibilities and advantages of digital technologies in sculpture are illustrated. It analyses the challenges that arise when using digital methods and highlights the importance of combining classical sculptural techniques and digital skills. Emphasising the importance of digital methods as tools that enrich and extend sculptural practice and create opportunities for achieving high quality and innovation in art.

Development of a Methodology for Obtaining Solid Models of Products That Are Objects of Reverse Engineering Using the Example of the Capstone Micro-GTU C 65

Currently, about a thousand micro gas turbine units of small and medium capacity are in operation in the Russian Federation, which are used as an autonomous power source at critical infrastructure facilities. During long-term operation, the component parts of the micro GTU may fail and require replacement or repair. The lack of spare parts and design documentation for their production makes it impossible to operate. As a way to solve the problem, the reverse engineering process can be used to produce components. One of the stages of reverse engineering is to determine the geometric parameters of the object. The fastest and most accurate way to obtain geometric characteristics in the reverse engineering process is 3D scanning. Three-dimensional scanning technology is used to obtain a solid 3D model of the prototype surface, based on which design documentation is subsequently developed. This article presents the results of a study of the influence of the parameters of the distance between polygonal grid points and the scanner exposure on the detailing of the outer surface and the geometric parameters of the resulting polygonal model. As a result of this study, the dependence of the final file size and the time spent on scanning and processing on the distance between the points of the polygonal grid and the model was established. Based on the dependence of the parameters, recommendations were obtained for choosing the distance between the points of the polygonal grid of laser 3D scanning. Also, after performing the stages of reverse engineering, the methodology for creating solid models and design documentation of parts of power equipment units using 3D scanning technology was improved.

Accuracy Assessment of Advanced Laser Scanner Technologies for Forest Survey Based on Three-Dimensional Point Cloud Data

Forests play a crucial role in carbon sequestration and climate change mitigation, offering ecosystem services, biodiversity conservation, and water resource management. As global efforts to reduce greenhouse gas emissions intensify, the demand for accurate spatial information to monitor forest conditions and assess carbon absorption capacity has grown. LiDAR (Light Detection and Ranging) has emerged as a transformative tool, providing high-resolution 3D spatial data for detailed analysis of forest attributes, including tree height, canopy structure, and biomass distribution. Unlike traditional manpower-intensive forest surveys, which are time-consuming and often limited in accuracy, LiDAR offers a more efficient and reliable solution. This study evaluates the accuracy and applicability of advanced LiDAR technologies—drone-mounted, terrestrial, and mobile scanners—for generating 3D forest spatial data. The results show that the terrestrial LiDAR achieved the highest precision for diameter at breast height (DBH) and tree height measurements, with RMSE values of 0.66 cm and 0.91 m, respectively. Drone-mounted LiDAR demonstrated excellent efficiency for large-scale surveys, while mobile LiDAR offered portability and speed but required further improvement in accuracy (e.g., RMSE: DBH 0.76 cm, tree height 1.83 m). By comparing these technologies, this study identifies their strengths, limitations, and optimal application scenarios, contributing to more accurate forest management practices and carbon absorption assessments.