This study introduces a novel method for reconstructing the 3D model of aluminum foam using cross-sectional sequence images.Combining precision milling and image acquisition,high-qual-ity cross-sectional images are ob...This study introduces a novel method for reconstructing the 3D model of aluminum foam using cross-sectional sequence images.Combining precision milling and image acquisition,high-qual-ity cross-sectional images are obtained.Pore structures are segmented by the U-shaped network(U-Net)neural network integrated with the Canny edge detection operator,ensuring accurate pore delineation and edge extraction.The trained U-Net achieves 98.55%accuracy.The 2D data are superimposed and processed into 3D point clouds,enabling reconstruction of the pore structure and aluminum skeleton.Analysis of pore 01 shows the cross-sectional area initially increases,and then decreases with milling depth,with a uniform point distribution of 40 per layer.The reconstructed model exhibits a porosity of 77.5%,with section overlap rates between the 2D pore segmentation and the reconstructed model exceeding 96%,confirming high fidelity.Equivalent sphere diameters decrease with size,averaging 1.95 mm.Compression simulations reveal that the stress-strain curve of the 3D reconstruction model of aluminum foam exhibits fluctuations,and the stresses in the reconstruction model concentrate on thin cell walls,leading to localized deformations.This method accurately restores the aluminum foam’s complex internal structure,improving reconstruction preci-sion and simulation reliability.The approach offers a cost-efficient,high-precision technique for optimizing material performance in engineering applications.展开更多
A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron micr...A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron microscope slices by Fou-rier-Bessel synthesis and electron tomography (ET), and a series of computed tomography (CT) was developed to perform si-multaneous measurement on the structure and function of biomedical samples. The paper presents the 3D reconstruction seg-mentation display and analysis results of pollen spore, chaperonin, virus, head, cervical bone, tibia and carpus. At the same time, it also puts forward some potential applications of the new technique in the biomedical realm.展开更多
The three-dimensional(3D)model is of great significance to analyze the performance of nonwovens.However,the existing modelling methods could not reconstruct the 3D structure of nonwovens at low cost.A new method based...The three-dimensional(3D)model is of great significance to analyze the performance of nonwovens.However,the existing modelling methods could not reconstruct the 3D structure of nonwovens at low cost.A new method based on deep learning was proposed to reconstruct 3D models of nonwovens from multi-focus images.A convolutional neural network was trained to extract clear fibers from sequence images.Image processing algorithms were used to obtain the radius,the central axis,and depth information of fibers from the extraction results.Based on this information,3D models were built in 3D space.Furthermore,self-developed algorithms optimized the central axis and depth of fibers,which made fibers more realistic and continuous.The method with lower cost could reconstruct 3D models of nonwovens conveniently.展开更多
Numerical simulation is the most powerful computational and analysis tool for a large variety of engineering and physical problems.For a complex problem relating to multi-field,multi-process and multi-scale,different ...Numerical simulation is the most powerful computational and analysis tool for a large variety of engineering and physical problems.For a complex problem relating to multi-field,multi-process and multi-scale,different computing tools have to be developed so as to solve particular fields at different scales and for different processes.Therefore,the integration of different types of software is inevitable.However,it is difficult to perform the transfer of the meshes and simulated results among software packages because of the lack of shared data formats or encrypted data formats.An image processing based method for three-dimensional model reconstruction for numerical simulation was proposed,which presents a solution to the integration problem by a series of slice or projection images obtained by the post-processing modules of the numerical simulation software.By means of mapping image pixels to meshes of either finite difference or finite element models,the geometry contour can be extracted to export the stereolithography model.The values of results,represented by color,can be deduced and assigned to the meshes.All the models with data can be directly or indirectly integrated into other software as a continued or new numerical simulation.The three-dimensional reconstruction method has been validated in numerical simulation of castings and case studies were provided in this study.展开更多
Structure reconstruction of 3 D anatomy from biplanar X-ray images is a challenging topic. Traditionally, the elastic-model-based method was used to reconstruct 3 D shapes by deforming the control points on the elasti...Structure reconstruction of 3 D anatomy from biplanar X-ray images is a challenging topic. Traditionally, the elastic-model-based method was used to reconstruct 3 D shapes by deforming the control points on the elastic mesh. However, the reconstructed shape is not smooth because the limited control points are only distributed on the edge of the elastic mesh.Alternatively, statistical-model-based methods, which include shape-model-based and intensity-model-based methods, are introduced due to their smooth reconstruction. However, both suffer from limitations. With the shape-model-based method, only the boundary profile is considered, leading to the loss of valid intensity information. For the intensity-based-method, the computation speed is slow because it needs to calculate the intensity distribution in each iteration. To address these issues, we propose a new reconstruction method using X-ray images and a specimen’s CT data. Specifically, the CT data provides both the shape mesh and the intensity model of the vertebra. Intensity model is used to generate the deformation field from X-ray images, while the shape model is used to generate the patient specific model by applying the calculated deformation field.Experiments on the public synthetic dataset and clinical dataset show that the average reconstruction errors are 1.1 mm and1.2 mm, separately. The average reconstruction time is 3 minutes.展开更多
With increasingly more smart cameras deployed in infrastructure and commercial buildings,3D reconstruction can quickly obtain cities’information and improve the efficiency of government services.Images collected in o...With increasingly more smart cameras deployed in infrastructure and commercial buildings,3D reconstruction can quickly obtain cities’information and improve the efficiency of government services.Images collected in outdoor hazy environments are prone to color distortion and low contrast;thus,the desired visual effect cannot be achieved and the difficulty of target detection is increased.Artificial intelligence(AI)solutions provide great help for dehazy images,which can automatically identify patterns or monitor the environment.Therefore,we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning.First,we propose a fine transmission image deep convolutional regression network(FT-DCRN)dehazing algorithm that uses fine transmission image and atmospheric light value to compute dehazed image.The DCRN is used to obtain the coarse transmission image,which can not only expand the receptive field of the network but also retain the features to maintain the nonlinearity of the overall network.The fine transmission image is obtained by refining the coarse transmission image using a guided filter.The atmospheric light value is estimated according to the position and brightness of the pixels in the original hazy image.Second,we use the dehazed images generated by the FT-DCRN dehazing algorithm for 3D reconstruction.An advanced relaxed iterative fine matching based on the structure from motion(ARI-SFM)algorithm is proposed.The ARISFM algorithm,which obtains the fine matching corner pairs and reduces the number of iterations,establishes an accurate one-to-one matching corner relationship.The experimental results show that our FT-DCRN dehazing algorithm improves the accuracy compared to other representative algorithms.In addition,the ARI-SFM algorithm guarantees the precision and improves the efficiency.展开更多
Abstract：reconstruction method using slice im-ages is proposed. Wanting to extract the outermost contours from slice images, the method of the improved GVF-Snake model with optimized force field and ray method is emp...Abstract：reconstruction method using slice im-ages is proposed. Wanting to extract the outermost contours from slice images, the method of the improved GVF-Snake model with optimized force field and ray method is employed. And then, the 3D model is reconstructed by contour connection using the im-proved shortest diagonal method and judgment function of contour fracture. The results show that the accuracy of reconstruction 3D model is improved.展开更多
Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering.This article introduces an innovative system for the thr...Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering.This article introduces an innovative system for the three-dimensional(3D)surface reconstruction of coarse aggregate particles using occlusion-free multi-view imaging.The system captures synchronized images of particles in free fall,employing a matte sphere and a nonlinear optimization approach to estimate the camera projection matrices.A pre-trained segmentation model is utilized to eliminate the background of the images.The Shape from Silhouettes(SfS)algorithm is then applied to generate 3D voxel data,followed by the Marching Cubes algorithm to construct the 3D surface contour.Validation against standard parts and diverse coarse aggregate particles confirms the method's high accuracy,with an average measurement precision of 0.434 mm and a significant increase in scanning and reconstruction efficiency.展开更多
3D reconstruction plays an increasingly important role in modern photogrammetric systems.Conventional satellite or aerial-based remote sensing(RS)platforms can provide the necessary data sources for the 3D reconstruct...3D reconstruction plays an increasingly important role in modern photogrammetric systems.Conventional satellite or aerial-based remote sensing(RS)platforms can provide the necessary data sources for the 3D reconstruction of large-scale landforms and cities.Even with low-altitude Unmanned Aerial Vehicles(UAVs),3D reconstruction in complicated situations,such as urban canyons and indoor scenes,is challenging due to frequent tracking failures between camera frames and high data collection costs.Recently,spherical images have been extensively used due to the capability of recording surrounding environments from one image.In contrast to perspective images with limited Field of View(FOV),spherical images can cover the whole scene with full horizontal and vertical FOV and facilitate camera tracking and data acquisition in these complex scenes.With the rapid evolution and extensive use of professional and consumer-grade spherical cameras,spherical images show great potential for the 3D modeling of urban and indoor scenes.Classical 3D reconstruction pipelines,however,cannot be directly used for spherical images.Besides,there exist few software packages that are designed for the 3D reconstruction from spherical images.As a result,this research provides a thorough survey of the state-of-the-art for 3D reconstruction from spherical images in terms of data acquisition,feature detection and matching,image orientation,and dense matching as well as presenting promising applications and discussing potential prospects.We anticipate that this study offers insightful clues to direct future research.展开更多
The focusing tomography is presented to reconstruct 3 dimensional irradiance distribution. A 3 dimensional luminous body could be considered as the combination of many 2 dimensional parallel luminous sections. Focu...The focusing tomography is presented to reconstruct 3 dimensional irradiance distribution. A 3 dimensional luminous body could be considered as the combination of many 2 dimensional parallel luminous sections. Focus on these discrete sections respectively by a single camera, a group of images would be captured to form governing equations of irradiance. After inversion procedure, the irradiance distribution of different sections could be decoded. In this experimentation two lightbulbs are used to simulate two luminous sections. Reasonable results demonstrate that this technique could be a useful method in irradiance reconstruction after further development.展开更多
3D medical image reconstruction has significantly enhanced diagnostic accuracy,yet the reliance on densely sampled projection data remains a major limitation in clinical practice.Sparse-angle X-ray imaging,though safe...3D medical image reconstruction has significantly enhanced diagnostic accuracy,yet the reliance on densely sampled projection data remains a major limitation in clinical practice.Sparse-angle X-ray imaging,though safer and faster,poses challenges for accurate volumetric reconstruction due to limited spatial information.This study proposes a 3D reconstruction neural network based on adaptive weight fusion(AdapFusionNet)to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images.To address the issue of spatial inconsistency in multi-angle image reconstruction,an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion,thereby improving the final reconstruction quality.The reconstruction network is built on an autoencoder(AE)framework and uses orthogonal-angle X-ray images(frontal and lateral projections)as inputs.The encoder extracts 2D features,which the decoder maps into 3D space.This study utilizes a lung CT dataset to obtain complete three-dimensional volumetric data,from which digitally reconstructed radiographs(DRR)are generated at various angles to simulate X-ray images.Since real-world clinical X-ray images rarely come with perfectly corresponding 3D“ground truth,”using CT scans as the three-dimensional reference effectively supports the training and evaluation of deep networks for sparse-angle X-ray 3D reconstruction.Experiments conducted on the LIDC-IDRI dataset with simulated X-ray images(DRR images)as training data demonstrate the superior performance of AdapFusionNet compared to other fusion methods.Quantitative results show that AdapFusionNet achieves SSIM,PSNR,and MAE values of 0.332,13.404,and 0.163,respectively,outperforming other methods(SingleViewNet:0.289,12.363,0.182;AvgFusionNet:0.306,13.384,0.159).Qualitative analysis further confirms that AdapFusionNet significantly enhances the reconstruction of lung and chest contours while effectively reducing noise during the reconstruction process.The findings demonstrate that AdapFusionNet offers significant advantages in 3D reconstruction of sparse-angle X-ray images.展开更多
This study examined the dynamic characteristics of upper airway collapse at soft palate level in patients with obstructive sleep apnea/hypopnea syndrome（OSAHS） by using dynamic 3-Dimensional（3-D） CT imaging.A tota...This study examined the dynamic characteristics of upper airway collapse at soft palate level in patients with obstructive sleep apnea/hypopnea syndrome（OSAHS） by using dynamic 3-Dimensional（3-D） CT imaging.A total of 41 male patients who presented with 2 of the following symptoms,i.e.,daytime sleepiness and fatigue,frequent snoring,and apnea with witness,were diagnosed as having OSAHS.They underwent full-night polysomnography and then dynamic 3-D CT imaging of the upper airway during quiet breathing and in Muller＇s maneuver.The soft palate length（SPL）,the minimal cross-sectional area of the retropalatal region（mXSA-RP）,and the vertical distance from the hard palate to the upper posterior part of the hyoid（hhL） were compared between the two breathing states.These parameters,together with hard palate length（HPL）,were also compared between mild/moderate and severe OSAHS groups.Association of these parameters with the severity of OSAHS [as reflected by apnea hypopnea index（AHI） and the lowest saturation of blood oxygen（LSaO2）] was examined.The results showed that 31 patients had severe OSAHS,and 10 mild/moderate OSAHS.All the patients had airway obstruction at soft palate level.mXSA-RP was significantly decreased and SPL remarkably increased during Muller＇s maneuver as compared with the quiet breathing state.There were no significant differences in these airway parameters（except the position of the hyoid bone） between severe and mild/moderate OSAHS groups.And no significant correlation between these airway parameters and the severity of OSAHS was found.The position of hyoid was lower in the severe OSAHS group than in the mild/moderate OSAHS group.The patients in group with body mass index（BMI）≥26 had higher collapse ratio of mXSA-RP,greater neck circumference and smaller mXSA-RP in the Muller＇s maneuver than those in group with BMI26（P0.05 for all）.It was concluded that dynamic 3-D CT imaging could dynamically show the upper airway changes at soft palate level in OSAHS patients.All the OSAHS patients had airway obstruction of various degrees at soft palate level.But no correlation was observed between the airway change at soft palate level and the severity of OSAHS.The patients in group with BMI≥26 were more likely to develop airway obstruction at soft palate level than those with BMI26.展开更多
Electrical impedance tomography(EIT)image reconstruction is a non-linear problem.In general,finite element model is the critical basis of EIT image reconstruction.A 3D human thorax modeling method for EIT image recons...Electrical impedance tomography(EIT)image reconstruction is a non-linear problem.In general,finite element model is the critical basis of EIT image reconstruction.A 3D human thorax modeling method for EIT image reconstruction is proposed herein to improve the accuracy and reduce the complexity of existing finite element modeling methods.The contours of human thorax and lungs are extracted from the layers of magnetic resonance imaging(MRI)images by an optimized Otsu’s method for the construction of the 3D human thorax model including the lung models.Furthermore,the GMSH tool is used for finite element subdivision to generate the 3D finite element model of human thorax.The proposed modeling method is fast and accurate,and it is universal for different types of MRI images.The effectiveness of the proposed method is validated by extensive numerical simulation in MATLAB.The results show that the individually oriented 3D finite element model can improve the reconstruction quality of the EIT images more effectively than the cylindrical model,the 2.5D model and other human chest models.展开更多
It is an active research area to reconstruct 3-D object and display its visible surfacesfrom cross-sectional images. In this paper, the methods of reconstructing 3-D object from medicalCT images and displaying the vis...It is an active research area to reconstruct 3-D object and display its visible surfacesfrom cross-sectional images. In this paper, the methods of reconstructing 3-D object from medicalCT images and displaying the visible surfaces are discussed. A polygon approximation methodthat forms polygon with the same number of segment points and a fast interpolation method forcross-sectional contours are presented at first. Then the voxel set of a human liver is reconstructed.And then the liver voxel set is displayed using depth and gradient shading methods. The softwareis written in C programming language at a microcomputer image processing system with a PC/ATcomputer as the host and a PC-VISION board as the image processing unit. The result of theprocessing is satisfying.展开更多
This paper proposes a practical algorithms of plane cutting, stereo clipping and arbitrary cutting for 3D surface model reconstructed from medical images. In plane cutting and stereo clipping algorithms, the 3D model ...This paper proposes a practical algorithms of plane cutting, stereo clipping and arbitrary cutting for 3D surface model reconstructed from medical images. In plane cutting and stereo clipping algorithms, the 3D model is cut by plane or polyhedron. Lists of edge and vertex in every cut plane are established. From these lists the boundary contours are created and their relationship of embrace is ascertained. The region closed by the contours is triangulated using Delaunay triangulation algorithm. Arbitrary cutting operation creates cutting curve interactively. The cut model still maintains its correct topology structure. With these operations, tissues inside can be observed easily and it can aid doctors to diagnose. The methods can also be used in surgery planning of radiotherapy.展开更多
The development of diagnostic imaging technology, such as multidetector computed tomography(MDCT) and magnetic resonance cholangiopancreatography(MRCP), has made it possible to obtain detailed images of the bile duct....The development of diagnostic imaging technology, such as multidetector computed tomography(MDCT) and magnetic resonance cholangiopancreatography(MRCP), has made it possible to obtain detailed images of the bile duct. Recent reports have indicated that a 3-dimensional(3D) reconstructed imaging system would be useful for understanding the liver anatomy before surgery. We have investigated a novel method that fuses MDCT and MRCP images. This novel system easily made it possible to detect the anatomical relationship between the vessels and bile duct in the portal hepatis. In this report, we describe a very rare case of extrahepatic cholangiocarcinoma associated with an accessory bile duct from the caudate lobe connecting with the intrapancreatic bile duct. We were unable to preoperatively detect this accessory bile duct using MDCT and MRCP. However, prior to the second operation, we were able to clearly visualise the injured accessory bile duct using our novel 3D imaging modality. In thisreport, we suggest that this imaging technique can be considered a novel and useful modality for understanding the anatomy of the portal hepatis, including the hilar bile duct.展开更多
Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral reso...Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional （3-D） feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures： Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling （RIBSR）method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution （A＆S） rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A＆S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.展开更多
In order to determine the structures of Si（111）-√7 √3-In surfaces and to understand their electronic properties, we construct six models of both hexagonal and rectangular types and perform first-principles calcula...In order to determine the structures of Si（111）-√7 √3-In surfaces and to understand their electronic properties, we construct six models of both hexagonal and rectangular types and perform first-principles calculations. Their scanning tunneling microscopic images and work functions are simulated and compared with experimental results. In this way, the hex-H3＇ and rect-T1 models are identified as the experimental configurations for the hexagonal and rectangular types, respectively. The structural evolution mechanism of the In/Si（lll） surface with indium coverage around 1.0 monolayer is discussed. The 4×1 and -√7× √3 phases are suggested to have two different types of evolution mechanisms, consistent with experimental results.展开更多
Fabric pilling evaluation has been considered as an essential element for textile quality inspection. Traditional manual method is still based on human eyes and brain, which is subjective with low efficiency. This pap...Fabric pilling evaluation has been considered as an essential element for textile quality inspection. Traditional manual method is still based on human eyes and brain, which is subjective with low efficiency. This paper proposes an objective evaluation method based on semi-calibrated near-light Photometric Stereo(PS). Fabric images are digitalized by self-developed image acquisition system. The 3D depth information of each point could be obtained by PS algorithm and then mapped to 2D grayscale image. After that, the non-textured image could be filtered by using the Gaussian low-pass filter. The pilling segmentation is conducted by using global iterative threshold segmentation method,and then K-Nearest Neighbor(KNN) is finally selected as a tool for the grade classification of fabric pilling. Our experimental results show that the proposed evaluation system could achieve excellent judging performance for the objective pilling evaluation.展开更多
Recently, orthogonal moments have become efficient tools for two-dimensional and three-dimensional（2D and 3D） image not only in pattern recognition, image vision, but also in image processing and applications engine...Recently, orthogonal moments have become efficient tools for two-dimensional and three-dimensional（2D and 3D） image not only in pattern recognition, image vision, but also in image processing and applications engineering. Yet, there is still a major difficulty in 3D rotation invariants. In this paper, we propose new sets of invariants for 2D and 3D rotation, scaling and translation based on orthogonal radial Hahn moments. We also present theoretical mathematics to derive them. Thus, this paper introduces in the first case new 2D radial Hahn moments based on polar representation of an object by one-dimensional orthogonal discrete Hahn polynomials, and a circular function. In the second case, we present new 3D radial Hahn moments using a spherical representation of volumetric image by one-dimensional orthogonal discrete Hahn polynomials and a spherical function. Further 2D and 3D invariants are derived from the proposed 2D and 3D radial Hahn moments respectively, which appear as the third case. In order to test the proposed approach, we have resolved three issues： the image reconstruction, the invariance of rotation, scaling and translation, and the pattern recognition. The result of experiments show that the Hahn moments have done better than the Krawtchouk moments, with and without noise. Simultaneously, the mentioned reconstruction converges quickly to the original image using 2D and 3D radial Hahn moments, and the test images are clearly recognized from a set of images that are available in COIL-20 database for 2D image, and Princeton shape benchmark（PSB） database for 3D image.展开更多
基金supported by the Key Research and DevelopmentPlan in Shanxi Province of China(No.201803D421045)the Natural Science Foundation of Shanxi Province(No.2021-0302-123104)。
文摘This study introduces a novel method for reconstructing the 3D model of aluminum foam using cross-sectional sequence images.Combining precision milling and image acquisition,high-qual-ity cross-sectional images are obtained.Pore structures are segmented by the U-shaped network(U-Net)neural network integrated with the Canny edge detection operator,ensuring accurate pore delineation and edge extraction.The trained U-Net achieves 98.55%accuracy.The 2D data are superimposed and processed into 3D point clouds,enabling reconstruction of the pore structure and aluminum skeleton.Analysis of pore 01 shows the cross-sectional area initially increases,and then decreases with milling depth,with a uniform point distribution of 40 per layer.The reconstructed model exhibits a porosity of 77.5%,with section overlap rates between the 2D pore segmentation and the reconstructed model exceeding 96%,confirming high fidelity.Equivalent sphere diameters decrease with size,averaging 1.95 mm.Compression simulations reveal that the stress-strain curve of the 3D reconstruction model of aluminum foam exhibits fluctuations,and the stresses in the reconstruction model concentrate on thin cell walls,leading to localized deformations.This method accurately restores the aluminum foam’s complex internal structure,improving reconstruction preci-sion and simulation reliability.The approach offers a cost-efficient,high-precision technique for optimizing material performance in engineering applications.
文摘A novel technique of three-dimensional (3D) reconstruction, segmentation, display and analysis of series slices of images including microscopic wide field optical sectioning by deconvolution method, cryo-electron microscope slices by Fou-rier-Bessel synthesis and electron tomography (ET), and a series of computed tomography (CT) was developed to perform si-multaneous measurement on the structure and function of biomedical samples. The paper presents the 3D reconstruction seg-mentation display and analysis results of pollen spore, chaperonin, virus, head, cervical bone, tibia and carpus. At the same time, it also puts forward some potential applications of the new technique in the biomedical realm.
基金National Natural Science Foundation of China(No.61771123)。
文摘The three-dimensional(3D)model is of great significance to analyze the performance of nonwovens.However,the existing modelling methods could not reconstruct the 3D structure of nonwovens at low cost.A new method based on deep learning was proposed to reconstruct 3D models of nonwovens from multi-focus images.A convolutional neural network was trained to extract clear fibers from sequence images.Image processing algorithms were used to obtain the radius,the central axis,and depth information of fibers from the extraction results.Based on this information,3D models were built in 3D space.Furthermore,self-developed algorithms optimized the central axis and depth of fibers,which made fibers more realistic and continuous.The method with lower cost could reconstruct 3D models of nonwovens conveniently.
基金funded by National Key R&D Program of China(No.2021YFB3401200)the National Natural Science Foundation of China(No.51875308)the Beijing Nature Sciences Fund-Haidian Originality Cooperation Project(L212002).
文摘Numerical simulation is the most powerful computational and analysis tool for a large variety of engineering and physical problems.For a complex problem relating to multi-field,multi-process and multi-scale,different computing tools have to be developed so as to solve particular fields at different scales and for different processes.Therefore,the integration of different types of software is inevitable.However,it is difficult to perform the transfer of the meshes and simulated results among software packages because of the lack of shared data formats or encrypted data formats.An image processing based method for three-dimensional model reconstruction for numerical simulation was proposed,which presents a solution to the integration problem by a series of slice or projection images obtained by the post-processing modules of the numerical simulation software.By means of mapping image pixels to meshes of either finite difference or finite element models,the geometry contour can be extracted to export the stereolithography model.The values of results,represented by color,can be deduced and assigned to the meshes.All the models with data can be directly or indirectly integrated into other software as a continued or new numerical simulation.The three-dimensional reconstruction method has been validated in numerical simulation of castings and case studies were provided in this study.
基金supported in part by The National Key Research and Development Program of China(2018YFC2001302)the National Natural Science Foundation of China(61976209)+1 种基金CAS International Collaboration Key Project(173211KYSB20190024)Strategic Priority Research Program of CAS(XDB32040000)。
文摘Structure reconstruction of 3 D anatomy from biplanar X-ray images is a challenging topic. Traditionally, the elastic-model-based method was used to reconstruct 3 D shapes by deforming the control points on the elastic mesh. However, the reconstructed shape is not smooth because the limited control points are only distributed on the edge of the elastic mesh.Alternatively, statistical-model-based methods, which include shape-model-based and intensity-model-based methods, are introduced due to their smooth reconstruction. However, both suffer from limitations. With the shape-model-based method, only the boundary profile is considered, leading to the loss of valid intensity information. For the intensity-based-method, the computation speed is slow because it needs to calculate the intensity distribution in each iteration. To address these issues, we propose a new reconstruction method using X-ray images and a specimen’s CT data. Specifically, the CT data provides both the shape mesh and the intensity model of the vertebra. Intensity model is used to generate the deformation field from X-ray images, while the shape model is used to generate the patient specific model by applying the calculated deformation field.Experiments on the public synthetic dataset and clinical dataset show that the average reconstruction errors are 1.1 mm and1.2 mm, separately. The average reconstruction time is 3 minutes.
基金supported in part by the National Natural Science Foundation of China under Grant 61902311in part by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(KAKENHI)under Grant JP18K18044.
文摘With increasingly more smart cameras deployed in infrastructure and commercial buildings,3D reconstruction can quickly obtain cities’information and improve the efficiency of government services.Images collected in outdoor hazy environments are prone to color distortion and low contrast;thus,the desired visual effect cannot be achieved and the difficulty of target detection is increased.Artificial intelligence(AI)solutions provide great help for dehazy images,which can automatically identify patterns or monitor the environment.Therefore,we propose a 3D reconstruction method of dehazed images for smart cities based on deep learning.First,we propose a fine transmission image deep convolutional regression network(FT-DCRN)dehazing algorithm that uses fine transmission image and atmospheric light value to compute dehazed image.The DCRN is used to obtain the coarse transmission image,which can not only expand the receptive field of the network but also retain the features to maintain the nonlinearity of the overall network.The fine transmission image is obtained by refining the coarse transmission image using a guided filter.The atmospheric light value is estimated according to the position and brightness of the pixels in the original hazy image.Second,we use the dehazed images generated by the FT-DCRN dehazing algorithm for 3D reconstruction.An advanced relaxed iterative fine matching based on the structure from motion(ARI-SFM)algorithm is proposed.The ARISFM algorithm,which obtains the fine matching corner pairs and reduces the number of iterations,establishes an accurate one-to-one matching corner relationship.The experimental results show that our FT-DCRN dehazing algorithm improves the accuracy compared to other representative algorithms.In addition,the ARI-SFM algorithm guarantees the precision and improves the efficiency.
基金Supported by National Natural Science Foundation of China(No.61272286)
文摘Abstract：reconstruction method using slice im-ages is proposed. Wanting to extract the outermost contours from slice images, the method of the improved GVF-Snake model with optimized force field and ray method is employed. And then, the 3D model is reconstructed by contour connection using the im-proved shortest diagonal method and judgment function of contour fracture. The results show that the accuracy of reconstruction 3D model is improved.
基金Supported by the Key R&D Projects in Shaanxi Province(2022JBGS3-08)。
文摘Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering.This article introduces an innovative system for the three-dimensional(3D)surface reconstruction of coarse aggregate particles using occlusion-free multi-view imaging.The system captures synchronized images of particles in free fall,employing a matte sphere and a nonlinear optimization approach to estimate the camera projection matrices.A pre-trained segmentation model is utilized to eliminate the background of the images.The Shape from Silhouettes(SfS)algorithm is then applied to generate 3D voxel data,followed by the Marching Cubes algorithm to construct the 3D surface contour.Validation against standard parts and diverse coarse aggregate particles confirms the method's high accuracy,with an average measurement precision of 0.434 mm and a significant increase in scanning and reconstruction efficiency.
基金funded by the National Natural Science Foundation of China[Grant No.42371442]the Hubei Provincial Natural Science Foundation of China[Grant No.2023AFB568]+1 种基金the Hong Kong Scholars Program[Grant No.2021-114]the Open Research fund from the Hubei Luojia Laboratory[Grand No.230100013].
文摘3D reconstruction plays an increasingly important role in modern photogrammetric systems.Conventional satellite or aerial-based remote sensing(RS)platforms can provide the necessary data sources for the 3D reconstruction of large-scale landforms and cities.Even with low-altitude Unmanned Aerial Vehicles(UAVs),3D reconstruction in complicated situations,such as urban canyons and indoor scenes,is challenging due to frequent tracking failures between camera frames and high data collection costs.Recently,spherical images have been extensively used due to the capability of recording surrounding environments from one image.In contrast to perspective images with limited Field of View(FOV),spherical images can cover the whole scene with full horizontal and vertical FOV and facilitate camera tracking and data acquisition in these complex scenes.With the rapid evolution and extensive use of professional and consumer-grade spherical cameras,spherical images show great potential for the 3D modeling of urban and indoor scenes.Classical 3D reconstruction pipelines,however,cannot be directly used for spherical images.Besides,there exist few software packages that are designed for the 3D reconstruction from spherical images.As a result,this research provides a thorough survey of the state-of-the-art for 3D reconstruction from spherical images in terms of data acquisition,feature detection and matching,image orientation,and dense matching as well as presenting promising applications and discussing potential prospects.We anticipate that this study offers insightful clues to direct future research.
文摘The focusing tomography is presented to reconstruct 3 dimensional irradiance distribution. A 3 dimensional luminous body could be considered as the combination of many 2 dimensional parallel luminous sections. Focus on these discrete sections respectively by a single camera, a group of images would be captured to form governing equations of irradiance. After inversion procedure, the irradiance distribution of different sections could be decoded. In this experimentation two lightbulbs are used to simulate two luminous sections. Reasonable results demonstrate that this technique could be a useful method in irradiance reconstruction after further development.
基金Supported by Sichuan Science and Technology Program(2023YFSY0026,2023YFH0004).
文摘3D medical image reconstruction has significantly enhanced diagnostic accuracy,yet the reliance on densely sampled projection data remains a major limitation in clinical practice.Sparse-angle X-ray imaging,though safer and faster,poses challenges for accurate volumetric reconstruction due to limited spatial information.This study proposes a 3D reconstruction neural network based on adaptive weight fusion(AdapFusionNet)to achieve high-quality 3D medical image reconstruction from sparse-angle X-ray images.To address the issue of spatial inconsistency in multi-angle image reconstruction,an innovative adaptive fusion module was designed to score initial reconstruction results during the inference stage and perform weighted fusion,thereby improving the final reconstruction quality.The reconstruction network is built on an autoencoder(AE)framework and uses orthogonal-angle X-ray images(frontal and lateral projections)as inputs.The encoder extracts 2D features,which the decoder maps into 3D space.This study utilizes a lung CT dataset to obtain complete three-dimensional volumetric data,from which digitally reconstructed radiographs(DRR)are generated at various angles to simulate X-ray images.Since real-world clinical X-ray images rarely come with perfectly corresponding 3D“ground truth,”using CT scans as the three-dimensional reference effectively supports the training and evaluation of deep networks for sparse-angle X-ray 3D reconstruction.Experiments conducted on the LIDC-IDRI dataset with simulated X-ray images(DRR images)as training data demonstrate the superior performance of AdapFusionNet compared to other fusion methods.Quantitative results show that AdapFusionNet achieves SSIM,PSNR,and MAE values of 0.332,13.404,and 0.163,respectively,outperforming other methods(SingleViewNet:0.289,12.363,0.182;AvgFusionNet:0.306,13.384,0.159).Qualitative analysis further confirms that AdapFusionNet significantly enhances the reconstruction of lung and chest contours while effectively reducing noise during the reconstruction process.The findings demonstrate that AdapFusionNet offers significant advantages in 3D reconstruction of sparse-angle X-ray images.
文摘This study examined the dynamic characteristics of upper airway collapse at soft palate level in patients with obstructive sleep apnea/hypopnea syndrome（OSAHS） by using dynamic 3-Dimensional（3-D） CT imaging.A total of 41 male patients who presented with 2 of the following symptoms,i.e.,daytime sleepiness and fatigue,frequent snoring,and apnea with witness,were diagnosed as having OSAHS.They underwent full-night polysomnography and then dynamic 3-D CT imaging of the upper airway during quiet breathing and in Muller＇s maneuver.The soft palate length（SPL）,the minimal cross-sectional area of the retropalatal region（mXSA-RP）,and the vertical distance from the hard palate to the upper posterior part of the hyoid（hhL） were compared between the two breathing states.These parameters,together with hard palate length（HPL）,were also compared between mild/moderate and severe OSAHS groups.Association of these parameters with the severity of OSAHS [as reflected by apnea hypopnea index（AHI） and the lowest saturation of blood oxygen（LSaO2）] was examined.The results showed that 31 patients had severe OSAHS,and 10 mild/moderate OSAHS.All the patients had airway obstruction at soft palate level.mXSA-RP was significantly decreased and SPL remarkably increased during Muller＇s maneuver as compared with the quiet breathing state.There were no significant differences in these airway parameters（except the position of the hyoid bone） between severe and mild/moderate OSAHS groups.And no significant correlation between these airway parameters and the severity of OSAHS was found.The position of hyoid was lower in the severe OSAHS group than in the mild/moderate OSAHS group.The patients in group with body mass index（BMI）≥26 had higher collapse ratio of mXSA-RP,greater neck circumference and smaller mXSA-RP in the Muller＇s maneuver than those in group with BMI26（P0.05 for all）.It was concluded that dynamic 3-D CT imaging could dynamically show the upper airway changes at soft palate level in OSAHS patients.All the OSAHS patients had airway obstruction of various degrees at soft palate level.But no correlation was observed between the airway change at soft palate level and the severity of OSAHS.The patients in group with BMI≥26 were more likely to develop airway obstruction at soft palate level than those with BMI26.
基金the National Natural Science Foundation of China(No.61371017)。
文摘Electrical impedance tomography(EIT)image reconstruction is a non-linear problem.In general,finite element model is the critical basis of EIT image reconstruction.A 3D human thorax modeling method for EIT image reconstruction is proposed herein to improve the accuracy and reduce the complexity of existing finite element modeling methods.The contours of human thorax and lungs are extracted from the layers of magnetic resonance imaging(MRI)images by an optimized Otsu’s method for the construction of the 3D human thorax model including the lung models.Furthermore,the GMSH tool is used for finite element subdivision to generate the 3D finite element model of human thorax.The proposed modeling method is fast and accurate,and it is universal for different types of MRI images.The effectiveness of the proposed method is validated by extensive numerical simulation in MATLAB.The results show that the individually oriented 3D finite element model can improve the reconstruction quality of the EIT images more effectively than the cylindrical model,the 2.5D model and other human chest models.
文摘It is an active research area to reconstruct 3-D object and display its visible surfacesfrom cross-sectional images. In this paper, the methods of reconstructing 3-D object from medicalCT images and displaying the visible surfaces are discussed. A polygon approximation methodthat forms polygon with the same number of segment points and a fast interpolation method forcross-sectional contours are presented at first. Then the voxel set of a human liver is reconstructed.And then the liver voxel set is displayed using depth and gradient shading methods. The softwareis written in C programming language at a microcomputer image processing system with a PC/ATcomputer as the host and a PC-VISION board as the image processing unit. The result of theprocessing is satisfying.
基金This research was supported by the National Nature Science Foundation of China under Grant No.60473024 the Nature Science Foundation of Zhejiang Province of China under Grant No.Y104341 and z105391.
文摘This paper proposes a practical algorithms of plane cutting, stereo clipping and arbitrary cutting for 3D surface model reconstructed from medical images. In plane cutting and stereo clipping algorithms, the 3D model is cut by plane or polyhedron. Lists of edge and vertex in every cut plane are established. From these lists the boundary contours are created and their relationship of embrace is ascertained. The region closed by the contours is triangulated using Delaunay triangulation algorithm. Arbitrary cutting operation creates cutting curve interactively. The cut model still maintains its correct topology structure. With these operations, tissues inside can be observed easily and it can aid doctors to diagnose. The methods can also be used in surgery planning of radiotherapy.
文摘The development of diagnostic imaging technology, such as multidetector computed tomography(MDCT) and magnetic resonance cholangiopancreatography(MRCP), has made it possible to obtain detailed images of the bile duct. Recent reports have indicated that a 3-dimensional(3D) reconstructed imaging system would be useful for understanding the liver anatomy before surgery. We have investigated a novel method that fuses MDCT and MRCP images. This novel system easily made it possible to detect the anatomical relationship between the vessels and bile duct in the portal hepatis. In this report, we describe a very rare case of extrahepatic cholangiocarcinoma associated with an accessory bile duct from the caudate lobe connecting with the intrapancreatic bile duct. We were unable to preoperatively detect this accessory bile duct using MDCT and MRCP. However, prior to the second operation, we were able to clearly visualise the injured accessory bile duct using our novel 3D imaging modality. In thisreport, we suggest that this imaging technique can be considered a novel and useful modality for understanding the anatomy of the portal hepatis, including the hilar bile duct.
文摘Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspeetral image. According to the characteristics and 3-Dimensional （3-D） feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures： Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling （RIBSR）method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution （A＆S） rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A＆S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.
基金V. ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China （No.20603032, No.20733004, No.21121003, No.91021004, No.20933006）, the National Key Basic Research Program （No.2011CB921400）, the Foundation of National Excellent Doctoral Dissertation of China （No.200736）, the Fundamental Research Funds for the Central Universities （No.WK2340000006 and No.WK2060140005）, and the Shanghai Supercompurer Center, the USTC-HP HPC Project, and the SCCAS.
文摘In order to determine the structures of Si（111）-√7 √3-In surfaces and to understand their electronic properties, we construct six models of both hexagonal and rectangular types and perform first-principles calculations. Their scanning tunneling microscopic images and work functions are simulated and compared with experimental results. In this way, the hex-H3＇ and rect-T1 models are identified as the experimental configurations for the hexagonal and rectangular types, respectively. The structural evolution mechanism of the In/Si（lll） surface with indium coverage around 1.0 monolayer is discussed. The 4×1 and -√7× √3 phases are suggested to have two different types of evolution mechanisms, consistent with experimental results.
基金Supported by the National Natural Science Foundation of China(61876106)。
文摘Fabric pilling evaluation has been considered as an essential element for textile quality inspection. Traditional manual method is still based on human eyes and brain, which is subjective with low efficiency. This paper proposes an objective evaluation method based on semi-calibrated near-light Photometric Stereo(PS). Fabric images are digitalized by self-developed image acquisition system. The 3D depth information of each point could be obtained by PS algorithm and then mapped to 2D grayscale image. After that, the non-textured image could be filtered by using the Gaussian low-pass filter. The pilling segmentation is conducted by using global iterative threshold segmentation method,and then K-Nearest Neighbor(KNN) is finally selected as a tool for the grade classification of fabric pilling. Our experimental results show that the proposed evaluation system could achieve excellent judging performance for the objective pilling evaluation.
文摘Recently, orthogonal moments have become efficient tools for two-dimensional and three-dimensional（2D and 3D） image not only in pattern recognition, image vision, but also in image processing and applications engineering. Yet, there is still a major difficulty in 3D rotation invariants. In this paper, we propose new sets of invariants for 2D and 3D rotation, scaling and translation based on orthogonal radial Hahn moments. We also present theoretical mathematics to derive them. Thus, this paper introduces in the first case new 2D radial Hahn moments based on polar representation of an object by one-dimensional orthogonal discrete Hahn polynomials, and a circular function. In the second case, we present new 3D radial Hahn moments using a spherical representation of volumetric image by one-dimensional orthogonal discrete Hahn polynomials and a spherical function. Further 2D and 3D invariants are derived from the proposed 2D and 3D radial Hahn moments respectively, which appear as the third case. In order to test the proposed approach, we have resolved three issues： the image reconstruction, the invariance of rotation, scaling and translation, and the pattern recognition. The result of experiments show that the Hahn moments have done better than the Krawtchouk moments, with and without noise. Simultaneously, the mentioned reconstruction converges quickly to the original image using 2D and 3D radial Hahn moments, and the test images are clearly recognized from a set of images that are available in COIL-20 database for 2D image, and Princeton shape benchmark（PSB） database for 3D image.
