Detailed 3D Information Research Articles

Integrating Cost-Effective Measurements and CFD Modeling for Accurate Air Quality Assessment

Assessing air quality in urban areas is vital for protecting public health, and low-cost sensor networks help quantify the population’s exposure to harmful pollutants effectively. This paper introduces an innovative method to calibrate air-quality sensor networks by combining CFD modeling with dependable AQ measurements. The developed CFD model is used to simulate traffic-related PM10 dispersion in a 1.6 × 2 km2 urban area. Hourly simulations are conducted, and the resulting concentrations are cross-validated against high-quality measurements. By offering detailed 3D information at a micro-scale, the CFD model enables the creation of concentration maps at sensor locations. Through regression analysis, relationships between low-cost sensor (LCS) readings and modeled outcomes are established and used for network calibration. The study demonstrates the methodology’s capability to provide aid to low-cost devices during a representative 24 h period. The precision of a CFD model can also guide optimal sensor placement based on prevailing meteorological and emission scenarios and refine existing networks for more accurate urban air quality representation. The usage of cost-effective air quality networks, high-quality monitoring stations, and high-resolution air quality modeling combines the strengths of both top-down and bottom-up approaches for air quality assessment. Therefore, the work demonstrated plays a significant role in providing reliable pollutant monitoring and supporting the assessment of environmental policies, aiming to address health issues related to urban air pollution.

Adaptive remanufacturing for freeform surface parts based on linear laser scanner and robotic laser cladding

Freeform surface parts play a significant role in the aerospace industry, the mold- manufacturing industry and the automobile industry, and it is energy-saving, material-saving, time-saving and environmentally beneficial to remanufacture the damaged components to restore their functionality and performance. Due to the complex geometry of the freeform surface wear, the adaptive remanufacturing of freeform surface parts is confronted with challenges. In this paper, an adaptive remanufacturing method for freeform surface parts based on linear laser scanner and robotic laser cladding is proposed to realize the precise freeform surface measurement and optimized remanufacturing path generation. On the one hand, a systematic wear measurement and assessment method is proposed to precisely locate and quantify the wear. With the noncontact calibration of the laser scanner and industrial robot, the contour of the target surface is real-timely measured and the reverse model is efficiently constructed, which provides detailed 3D morphological information of the worn freeform surface for the latter wear analysis. Next, considering the considerable difference between the reverse model and the nominal model, a refined model aligning method weighted by surface wear segmentation is proposed to minimize the alignment error and, further, the difference entity to be additively manufactured is obtained by discrete model comparison. On the other hand, to cope with the unsatisfactory binding strength over the freeform surface basis and small fragments of the working path for the traditional plane or cylinder slicing method, a novel remanufacturing path generation method is proposed. Considering the curvature distribution of the freeform surface, an optimized equidistant freeform surface slicing method is especially proposed for the difference entity to realize the adaptive fitting to the freeform basin. Furthermore, based on the equivalent volume overlapping model of laser cladding, the cladding track filling method for the freeform surface slicing is designed with the optimized track-to-track distance, which can reduce surface waviness and improve remanufacturing efficiency. Finally, simulations and experiments for the remanufacturing scenario of the steam turbine blade are conducted to verify the validity and feasibility of the proposed adaptive remanufacturing method for freeform surface parts based on linear laser scanner and robotic laser cladding.

Measurements and Protocols Used for Weight-Bearing Cone-Beam CT Scans for Evaluating the Alignment of the Foot and Ankle: A Systematic Literature Review

Category: Hindfoot; Midfoot/Forefoot Introduction/Purpose: Weight bearing CT has been widely used recently to provide detailed 3D information of the foot and ankle. Orthopedic surgeons have been exposed to this new technology, but do not have the equivalent tools to use to explore it. A lot of metrics were directly borrowed from plain radiographic imaging, while some new parameters were developed using traditional axes and angular concepts but on only one specific WBCT view out of hundreds of scans. Some metrics used similar measurement concepts, but on 3D reconstructed bones, while a few new parameters were introduced based on semi 3D and 3D thinking. Small sample sizes, obscure inclusion/exclusion criteria, and skewed validation methods are noted, and a thorough review of WBCT-based measurements used in foot and ankle is warranted. Methods: A literature search was conducted in two databases: PubMed (MEDLINE) and EMBASE (Elsevier). The main search terms and logics were: ((foot) OR (ankle) OR (hindfoot) OR (midfoot) OR (forefoot)) AND ((WBCT) OR (Weightbearing CT) OR (Cone beam CT scan) OR (PedCAT)). A longer string of key words was utilized to further narrow down the results to WBCT imaging associated with foot and ankle pathologies. The terms were expanded using the MeSH and Emtree expansion features of PubMed and EMBASE, respectively. All articles were reviewed by two independent senior foot and ankle surgeons based on pre-designed exclusion criteria. Off-topic articles were removed, and remaining articles were categorized based on measurement techniques. All articles were managed using Zotero. (Figure 1) Results: A total of 216 articles were selected for retrieval and further organized by measurement techniques. Seven groups were set by the type of the methodology used. Among them, 123 studies utilized traditional 2D measurement parameters (eg, hindfoot moment arm, Meary’s angle, talonavicular uncoverage, hallux valgus angle, etc.), 8 introduced new parameters but based on 2D axial/angular concepts (eg, middle facet subluxation percentage and angle), 22 used semi-automated 3D measurement techniques (3D segmentation + 2D axial and angular methods), 19 using semi-3D measurement techniques (Foot and Ankle Offset), 29 measured real 3D parameters (volume evaluation in the syndesmosis and Lisfranc joints, distance mapping), 3 morphological studies used 3D segmentation and sphere fitting. The advantages and disadvantages of each type of measurement were carefully examined and explored. Conclusion: 3D imaging measurements with WBCT appear to be highly variegated. Axial and angular measurements do not apply well to irregular bones and there is a low reproducibility in 3D scenarios. Although inter- and intraobserver reproducibility scores have been reported in multiple studies, they were only part of the validation system that should be done. A high correlation between parameters such as 2D and 3D hindfoot angles has been reported, but debate remains as to whether one method of measurement is more accurate than the other. Furthermore, variations in analytical methods warrant a more uniformly defined coordinate or anatomical system.

A Robotized Soft Endoscope with Stereo Vision for Upper Gastrointestinal Endoscopic Submucosal Dissection (ESD).

This work presents a novel dual-segment flexible robotic endoscope designed to enhance reachability and dexterity during ESD surgery. The proposed system is capable of executing multi-angle cutting operations at a small angle relative to the lesion surface, allowing for efficient en-bloc resection. Additionally, the system incorporates two calibrated RGB cameras and a depth estimation algorithm to provide detailed 3D information of the tumour, which is used to guide the control framework. A stereo visual servoing controller is also implemented to improve path-following performance during surgery. Experiments results indicate that the proposed system improves motion stability and precision. The root means square error (RMSE) of circle path following is 1.1991mm with a maximum of 1.4751mm. Ex-vivo testing demonstrates its significant potential for use in endoscopic surgery.

Fast and Accurate Simulation of Canopy Reflectance under Wavelength-Dependent Optical Properties Using a Semi-Empirical 3D Radiative Transfer Model

Generating canopy-reflectance datasets using radiative transfer models under various leaf and soil optical property combinations is important for remote sensing retrieval of vegetation parameters. One-dimensional radiative transfer models have been frequently used. However, three-dimensional (3D) models usually require detailed 3D information that is difficult to obtain and long model execution time, limiting their use in remote sensing applications. This study aims to address these limitations for practical use of 3D models, proposing a semi-empirical speed-up method for canopy-reflectance simulation based on a LargE-Scale remote sensing data and image Simulation model (LESS), called Semi-LESS. The speed-up method is coupled with 3D LESS to describe the dependency of canopy reflectance on the wavelength, leaf, soil, and branch optical properties for a scene with fixed 3D structures and observation/illumination configurations, allowing fast generating accurate reflectance images under various wavelength-dependent optical parameters. The precomputed dataset stores simulated multispectral coefficient images under few predefined soil, branch, and leaf optical properties for each RAdiation transfer Model Intercomparison-V scene, which can then be used alone to compute reflectance images on the fly without the participation of LESS. Semi-LESS has been validated with full 3D radiative-transfer-simulated images, showing very high accuracy (root mean square error < 0.0003). The generation of images using Semi-LESS is much more efficient than full LESS simulations with an acceleration of more than 320 times. This study is a step further to promote 3D radiative transfer models in practical remote sensing applications such as vegetation parameter inversions.

Разработка алгоритма семантической сегментации на основе признаков для разделения наземных и неназемных поверхностей

Recent advances in remote sensing technology make it possible to digitize the real world almost automatically. Airborne laser scan results are georeferenced data type. They provide detailed 3D information about objects and the environment. Automated classification and detection of objects obtained from lidar is necessary to minimize production costs. Although the optimization of traditional methods using rule-based algorithms has expanded geospatial applications, significant manual editing is still required to obtain a high quality data set. Unlike images, point arrays are unstructured, sparse, and have a non-standard data format. This creates a lot of challenges, but it also provides a huge opportunity to capture the details of scanned surfaces with millimeter accuracy. Classifying and separating non-ground points from ground points greatly reduces the amount of data required for consistent surface analysis, saving time and simplifying further analysis. The main idea of scientific research is to use deep learning as a section of machine learning to analyze an array of points. The paper presents a feature-based algorithm that classifies ground and non-ground points in airborne laser scanning cloud.

Elastic 3D–2D Image Registration

We propose a method to nonrigidly align a three-dimensional (3D) volumetric image with a two-dimensional (2D) planar image representing a projection of the deformed volume. The application in mind comes from biological studies in which 2D intravital microscopy videos of living tissue are recorded, after which the tissue is excised and a more detailed 3D volume microscopy is performed. Coregistration of both data sets allows to combine the temporal (but 2D) information with more detailed spatial 3D information. Our approach is variational and uses a hyperelastic deformation regularization, as is appropriate for biological material. As a particular feature, the out-of-plane deformation is estimated based on the out-of-focus blur inside the 2D microscopy image. The approach becomes computationally feasible through the use of a coarse-to-fine optimization strategy and higher-order optimization methods.

Fast 4D On-the-Fly Tomography for Observation of Advanced Pore Morphology (APM) Foam Elements Subjected to Compressive Loading.

Observation of dynamic testing by means of X-ray computed tomography (CT) and in-situ loading devices has proven its importance in material analysis already, yielding detailed 3D information on the internal structure of the object of interest and its changes during the experiment. However, the acquisition of the tomographic projections is, in general, a time-consuming task. The standard method for such experiments is the time-lapse CT, where the loading is suspended for the CT scan. On the other hand, modern X-ray tubes and detectors allow for shorter exposure times with an acceptable image quality. Consequently, the experiment can be designed in a way so that the mechanical test is running continuously, as well as the rotational platform, and the radiographic projections are taken one after another in a fast, free-running mode. Performing this so-called on-the-fly CT, the time for the experiment can be reduced substantially, compared to the time-lapse CT. In this paper, the advanced pore morphology (APM) foam elements were used as the test objects for in-situ X-ray microtomography experiments, during which series of CT scans were acquired, each with the duration of 12 s. The contrast-to-noise ratio and the full-width-half-maximum parameters are used for the quality assessment of the resultant 3D models. A comparison to the 3D models obtained by time-lapse CT is provided.

X-Ray Phase Contrast 3D Virtual Histology: Evaluation of Lung Alterations After Microbeam Irradiation

This study provides the first experimental application of multiscale 3-dimensional (3D) x-ray phase contrast imaging computed tomography (XPCI-CT) virtual histology for the inspection and quantitative assessment of the late-stage effects of radio-induced lesions on lungs in a small animal model. Healthy male Fischer rats were irradiated with x-ray standard broad beams and microbeam radiation therapy, a high-dose rate (14 kGy/s), FLASH spatially fractionated x-ray therapy to avoid beamlet smearing owing to cardiosynchronous movements of the organs during the irradiation. After organ dissection, ex vivo XPCI-CT was applied to all the samples and the results were quantitatively analyzed and correlated to histologic data. XPCI-CT enables the 3D visualization of lung tissues with unprecedented contrast and sensitivity, allowing alveoli, vessel, and bronchi hierarchical visualization. XPCI-CT discriminates in 3D radio-induced lesions such as fibrotic scars and Ca/Fe deposits and allows full-organ accurate quantification of the fibrotic tissue within the irradiated organs. The radiation-induced fibrotic tissue content is less than 10% of the analyzed volume for all microbeam radiation therapy-treated organs and reaches 34% in the case of irradiations with 50 Gy using a broad beam. XPCI-CT is an effective imaging technique able to provide detailed 3D information for the assessment of lung pathology and treatment efficacy in a small animal model.

3D visualization and morphometric analysis of spinal motion segments and vascular networks: A synchrotron radiation-based micro-CT study in mice.

The structure of spinal motion segments and spinal vasculature is complicated. Visualizing the three-dimensional (3D) structure of the spine may provide guidance for spine surgery. However, conventional imaging techniques fail to simultaneously obtain 3D images of soft and hard tissues, and achieving such coimaging states of the spine and its vascular networks remains a challenge. Synchrotron radiation micro-CT (SRμCT) provides a relatively effective and novel method of acquiring detailed 3D information. In this study, specimens of the thoracic spine were obtained from six mice. SRμCT was employed to acquire 3D images of the structure, and histologic staining was performed for comparisons with the SRμCT images. The whole spinal motion segments and the spinal vascular network were simultaneously explored at high resolution. The mean thickness of the cartilaginous end plates (CEPs) and the volume of the intervertebral discs (IVDs) were calculated. The surface of the CEPs and the facet joint cartilage (FJC) were presented as heat maps, which allowed for direct visualization of the thickness distribution. Regional division revealed heterogeneity among the ventral, central, and dorsal parts of the CEPs and between the superior and inferior parts of the facet processes. Moreover, the connections and spatial morphology of the spinal vascular network were visualized. Our study indicates that SRμCT imaging is an ideal method for high-resolution visualization and 3D morphometric analysis of the whole spinal motion segments and spinal vascular network.

A Review of Augmented Reality Applications in Civil Infrastructure During the 4th Industrial Revolution

The 4th industrial revolution started in 2016 and referred to a new phase in the industrial revolution. One of the most significant technological evolvements during the 4th industrial revolution is Augmented Reality (AR) technology. AR superimposes interactional virtual objects/images to real environments. Because of the interaction and see-through characteristics, AR is better applied to engineering than Virtual Reality (VR). The application of AR in civil infrastructure can avoid artificial mistakes, improve efficiency, and saves budget. This article reviews AR applications in civil infrastructure, focusing on research studies in the latest five years (2016–2020) and their milestone developments. More than half of the AR research and implementation studies have focused on the construction domain in the last five years. Researchers deploy AR technologies in on-site construction to assist in discrepancy checking, collaborative communication, and safety checking. AR also uses building information models (BIMs) to produce detailed 3D structural information for visualization. Additionally, AR has been studied for structural health monitoring (SHM), routine and damage detection, energy performance assessment, crack inspection, excavation, and underground utility maintenance. Finally, AR has also been applied for architecture design, city plan, and disaster prediction as an essential part of smart city service. This article discusses the challenges of AR implementation in civil infrastructure and recommends future applications.

Extrinsic Calibration of Dual LiDARs Based on Plane Features and Uncertainty Analysis

Solutions equipped with two or more light detection and ranging (LiDAR) systems have been applied in several fields (navigation, mapping, target detection, and others) to obtain increasingly detailed 3D environmental information. Accurate calibration of multiple LiDAR systems is necessary for integrating and using their data. This study improves a convenient and reliable method for calibrating the relative poses between 3D LiDARs. The planar surfaces of a scene are measured from different poses; then, the planes are extracted and constraints are constructed to solve extrinsic parameters. The factors influencing calibration uncertainty are also investigated. It is found that the uncertainty is closely related to the geometric structure of the plane observations, and the rotation dilution of precision and translation dilution of precision are defined to denote this effect. The influence of different types of spatial plane geometries on calibration errors is discussed, and optimal observation conditions are derived. Experimental results for simulation and real data show that the proposed method can achieve an accurate extrinsic calibration of LiDARs, and the point cloud registration errors after calibration are less than 2 cm. The analysis of the calibration uncertainty provides a valuable reference and guide for experimental design and error evaluation.

Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin.

Fragment screening is a technique that helps to identify promising starting points for ligand design. Given that crystals of the target protein are available and display reproducibly high-resolution X-ray diffraction properties, crystallography is among the most preferred methods for fragment screening because of its sensitivity. Additionally, it is the only method providing detailed 3D information of the binding mode of the fragment, which is vital for subsequent rational compound evolution. The routine use of the method depends on the availability of suitable fragment libraries, dedicated means to handle large numbers of samples, state-of-the-art synchrotron beamlines for fast diffraction measurements and largely automated solutions for the analysis of the results. Here, the complete practical workflow and the included tools on how to conduct crystallographic fragment screening (CFS) at the Helmholtz-Zentrum Berlin (HZB) are presented. Preceding this workflow, crystal soaking conditions as well as data collection strategies are optimized for reproducible crystallographic experiments. Then, typically in a one to two-day procedure, a 96-membered CFS-focused library provided as dried ready-to-use plates is employed to soak 192 crystals, which are then flash-cooled individually. The final diffraction experiments can be performed within one day at the robot-mounting supported beamlines BL14.1 and BL14.2 at the BESSY II electron storage ring operated by the HZB in Berlin-Adlershof (Germany). Processing of the crystallographic data, refinement of the protein structures, and hit identification is fast and largely automated using specialized software pipelines on dedicated servers, requiring little user input. Using the CFS workflow at the HZB enables routine screening experiments. It increases the chances for successful identification of fragment hits as starting points to develop more potent binders, useful for pharmacological or biochemical applications.

Models of cultural heritage buildings in a procedurally generated geospatial environment

AbstractThis article presents a methodology combining building information modelling, CAD, procedural modelling, 3D GIS, and digital cartography to create information models of cultural heritage buildings and their geospatial environments both in history and nowadays. The results of the workflow are 3D web scenes where the most historically significant buildings are presented as detailed 3D textured information models. These models consist of 3D representations of specific architectural elements, which contain semantic information and attributes. Other valuable buildings are modelled classically in CAD and they can be identified as one complete object each, and thus the users can view concise information about the history and important aspects of the buildings. Finally, the common conurbation is generated procedurally. The 3D visualizations can be viewed in a web browser without any plugins needed, and can familiarize users from the general public with the architectural structure of the objects of interest and their environment.

Verification of stereotactic cranial radiotherapy treatments with MR-based gel dosimeters: practical aspects

Image Guided Radiotherapy (IGRT) systems allow delivering high doses of radiation to a tumour with great precision and accuracy. In this work, we use patient-specific head MR-based gel dosimeters as an end-to-end test to commission IGRT delivery systems, for stereotactic cranial radiotherapy, and investigate possible sources of errors associated with practical aspects of the measurements. A CT scan of a patient is used to 3D print the shape of the cranial bones to create head phantoms with MR-based gel inside. Each phantom was used as a patient, following the radiotherapy workflow which includes: taking a CT scan of the phantom, calculating the dose distribution using a treatment planning system (TPS) and delivering the radiation calculated by the TPS (to target three different lesions: Big, Medium and Small). Each phantom was then scanned on an MR scanner to obtain a T2 map (linear with dose), which was then rigidly registered with the CT scan of the phantom based on the phantom structures. Good agreement was obtained between the normalized R2 (=1/T2) values and TPS simulations. The relationship between R2 values and dose was investigated based on 3D regions including each lesion. Good linearity was found, but different R2-dose values relationship was obtained depending on the selected regions. The impact of applying a registration based on each lesion (and not the phantom structures) was also tested. Results show that the registration has an impact on the relationship between R2 values and dose, and although absolute dose measurements are still not possible with these MR-based gel dosimeters, they provide very detailed geometrical 3D information to validate IGRT radiotherapy treatments with high level of accuracy.

Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds

Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra–taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE%) for tree heights (mean R2 = 0.77, mean RMSE% = 18.46%) than for crown diameters (mean R2 = 0.46, mean RMSE% = 24.9%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra–taiga ecotone should be adapted to the forest structure and have a radius of >15–20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest’s stand structure.

TRAJECTORY-BASED VISUALIZATION OF MMS POINT CLOUDS

Abstract. MMSs allow us to obtain detailed 3D information around roads. Especially, LiDAR point clouds can be used for map generation and infrastructure management. For practical uses, however, it is necessary to add labels to a part of the points since various objects can be included in the point clouds. Existing automatic classification methods are not completely error-free, and may incorrectly classify objects. Therefore, even though automatic methods are applied to the point clouds, operators have to verify the labels. While operators classify the point clouds manually, selecting 3D points tasks in 3D views are difficult. In this paper, we propose a new point-cloud image based on the trajectories of MMSs. We call our point-cloud image trajectory-based point-cloud image. Although the image is distorted because it is generated based on rotation angles of laser scanners, we confirmed that most objects can be recognized from point-cloud images by checking main road facilities. We evaluated how efficient the annotation can be done using our method, and the results show that operators could add annotations to point-cloud images more efficiently.

Operational Deflection Shape Extraction from Broadband Events of an Aircraft Component Using 3D‐DIC in Magnified Images

Recently, many works have shown the capabilities of noninterferometric optical techniques, such as digital image correlation, to characterise modal behaviour. They provide a global insight into the structure or component behaviour which implies massive spatial information, unaffordable by traditional sensor instrumentation. Moreover, phase‐based motion magnification (PMM) is a methodology which, based on a sequence of images, magnifies a periodic motion encoded in phase time‐domain signals of the complex steerable pyramid filters employed to decompose the images. It provides a powerful tool to interpret deformation. However, the interpretation is just qualitative and should be avoided if out‐plane motion is recorded as only one camera is employed. To overcome this issue, 3D digital image correlation (3D‐DIC) has been linked with PMM to provide measurements from stereoscopic sets of images, providing full‐field displacement maps to magnified images. In this work, the combination of PMM and 3D‐DIC has been employed to evaluate the modal behaviour of an aircraft cabin under random excitation. The study was focused on the passenger window area due to its significance to the structural integrity as a discontinuity of the peel. Operational deflection shapes at different resonances were characterised by magnifying a single resonance in the spectrum and then measuring with 3D‐DIC. These measurements were validated with those obtained in forced normal mode tests. Motion and displacement videos improved the understanding of the identified resonance deformation. Actually, a relevant behaviour was noticed in the window’s frame, a quite narrow area where using traditional sensors would not provide such a detailed 3D information.

Deep learning-based digital in-line holographic microscopy for high resolution with extended field of view

A digital in-line holographic microscopy (DIHM) with deep learning-based upscaling method is proposed to overcome the trade-off between high resolving power and large field-of-view (FOV). To enhance the spatial resolution of a hologram, a deep neural network was trained with hologram images, which are defocused images with diffraction patterns. The performance of the artificial intelligence-based DIHM method was verified using hologram images obtained by computer simulation and experiments. Upscaled holograms with enhanced image contrast and clear diffraction pattern provided high quality of reconstructed holograms. In addition to the enhancement of reconstructed image at the sample position, details of light scattering pattern could be revealed with the proposed method. The proposed deep learning-based DIHM method is promising for accurate monitoring of many samples and analyzing dynamics of particles or cells in large FOV with detailed 3D information reconstructed from the upscaled holograms.

Quantitative characterization of high temperature oxidation using electron tomography and energy-dispersive X-ray spectroscopy

We report quantitative characterization of the high temperature oxidation process by using electron tomography and energy-dispersive X-ray spectroscopy. As a proof of principle, we performed 3D imaging of the oxidation layer of a model system (Mo3Si) at nanoscale resolution with elemental specificity and probed the oxidation kinetics as a function of the oxidation time and the elevated temperature. Our tomographic reconstructions provide detailed 3D structural information of the surface oxidation layer of the Mo3Si system, revealing the evolution of oxidation behavior of Mo3Si from early stage to mature stage. Based on the relative rate of oxidation of Mo3Si, the volatilization rate of MoO3 and reactive molecular dynamics simulations, we propose a model to explain the mechanism of the formation of the porous silica structure during the oxidation process of Mo3Si. We expect that this 3D quantitative characterization method can be applied to other material systems to probe their structure-property relationships in different environments.