BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and H...BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.展开更多
In many cases,the Digital Surface Models(DSMs)and Digital Elevation Models(DEMs)are obtained with Light Detection and Ranging(LiDAR)or stereo matching.As an active method,LiDAR is very accurate but expensive,thus ofte...In many cases,the Digital Surface Models(DSMs)and Digital Elevation Models(DEMs)are obtained with Light Detection and Ranging(LiDAR)or stereo matching.As an active method,LiDAR is very accurate but expensive,thus often limiting its use in small-scale acquisition.Stereo matching is suitable for large-scale acquisition of terrain information as the increase of satellite stereo sensors.However,underperformance of stereo matching easily occurs in textureless areas.Accordingly,this study proposed a Shading Aware DSM GEneration Method(SADGE)with high resolution multi-view satellite images.Considering the complementarity of stereo matching and Shape from Shading(SfS),SADGE combines the advantage of stereo matching and SfS technique.First,an improved Semi-Global Matching(SGM)technique is used to generate an initial surface expressed by a DSM;then,it is refined by optimizing the objective function which modeled the imaging process with the illumination,surface albedo,and normal object surface.Different from the existing shading-based DEM refinement or generation method,no information about the illumination or the viewing angle is needed while concave/convex ambiguity can be avoided as multi-view images are utilized.Experiments with ZiYuan-3 and GaoFen-7 images show that the proposed method can generate higher accuracy DSM(12.5-56.3%improvement)with sound overall shape and temporarily detailed surface compared with a software solution(SURE)for multi-view stereo.展开更多
Mesoscopy refers to imaging methodologies that provide a field of view(FOV)ranging from several millimeters to centimeters while achieving cellular or even subcellular resolution(Figure 1).This technological framework...Mesoscopy refers to imaging methodologies that provide a field of view(FOV)ranging from several millimeters to centimeters while achieving cellular or even subcellular resolution(Figure 1).This technological framework employs specially designed large-scale objective lenses to correct aberrations across extended FOVs,synchronized with light-field acquisition modalities through either scanning point detection or large-format array detection.Conventional microscopes,constrained by the limitations of objective lenses,exhibit a trade-off between the FOV and resolution.To achieve both high resolution and a large FOV,common approaches such as FOV stitching and Fourier ptychography were employed.However,these methods were extremely slow and imposed numerous constraints on samples.In 2016,a mesoscopic objective lens was introduced to address these challenges,achieving a 6 mm FOV and 0.7 mm resolution,thereby increasing the imaging throughput of conventional objective lenses by orders of magnitude.1 In the same year,this technology was recognized as one of the top ten physics breakthroughs worldwide by Physics World.Since then,mesoscopic imaging technology has gradually gained momentum and has been applied in various fields.展开更多
Introduction of the stepwise phase dispersion compensation layer allowed broadband achromatic metalens to have a high numerical aperture,which enabled high-resolution metalens imaging.
The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resoluti...The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images,we present an effective YOLOv3 framework,corner regression-based YOLOv3(Correg-YOLOv3),to localize dense building accurately.This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box.By extending output dimensions,the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile.Finally,we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively.The experimental results achieve high performance in precision(96.45%),recall rate(95.75%),F1 score(96.10%)and average precision(98.05%),which were 2.73%,5.4%,4.1%and 4.73%higher than that of YOLOv3.Therefore,our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.展开更多
Road extraction plays an important role in many applications such as car navigation, but the manual extraction of roads is a laborious, tedious task. To speed the extraction of roads, an approach based on particle fil...Road extraction plays an important role in many applications such as car navigation, but the manual extraction of roads is a laborious, tedious task. To speed the extraction of roads, an approach based on particle filtering to extract automatically roads from high resolution imagery is proposed. Particle filtering provides a statistical framework for propagating sample-based approximations of posterior distributions and has almost no restriction on the ingredients of the model. We integrate the similarity of grey value and the edge point distribution of roads into particle filtering to deal with complex scenes. To handle road appearance changes the tracking algorithm is allowed to update the road model during temporally stable image observations. A fully automatic initialization strategy is used. Experimental results show that the proposed approach is a promising and fully automatic method for extracting roads from images, even in the presence of occlusions.展开更多
Small-object detection has long been a challenge.High-megapixel cameras are used to solve this problem in industries.However,current detectors are inefficient for high-resolution images.In this work,we propose a new m...Small-object detection has long been a challenge.High-megapixel cameras are used to solve this problem in industries.However,current detectors are inefficient for high-resolution images.In this work,we propose a new module called Pre-Locate Net,which is a plug-and-play structure that can be combined with most popular detectors.We inspire the use of classification ideas to obtain candidate regions in images,greatly reducing the amount of calculation,and thus achieving rapid detection in high-resolution images.Pre-Locate Net mainly includes two parts,candidate region classification and behavior classification.Candidate region classification is used to obtain a candidate region,and behavior classification is used to estimate the scale of an object.Different follow-up processing is adopted according to different scales to balance the variance of the network input.Different from the popular candidate region generation method,we abandon the idea of regression of a bounding box and adopt the concept of classification,so as to realize the prediction of a candidate region in the shallow network.We build a high-resolution dataset of aircraft and landing gears covering complex scenes to verify the effectiveness of our method.Compared to state-of-the-art detectors(e.g.,Guided Anchoring,Libra-RCNN,and FASF),our method achieves the best m AP of 94.5 on 1920×1080 images at 16.7 FPS.展开更多
The dispersoid phase Al_(20)Cu_2Mn_3 in a 2024 Al alloy is commonly composed of twins,An ob- servation of corresponding high resolution image shows that the twin boundary plane is a glide plane other than mirror one.T...The dispersoid phase Al_(20)Cu_2Mn_3 in a 2024 Al alloy is commonly composed of twins,An ob- servation of corresponding high resolution image shows that the twin boundary plane is a glide plane other than mirror one.Two neighbouring components of twins are not symmetry of re- flection or rotation,but of glide reflection.The“diamond”glide plane is(101)and the glide vector is(1/4)(-).Components of twins in the phase take shape of prism with the longitudinal edge being parallel to[010]and side faces being{101}and{100}.展开更多
Accurate information on the location and magnitude of vegetation change in scenic areas can guide the configuration of tourism facilities and the formulation of vegetation protection measures.High spatial resolution r...Accurate information on the location and magnitude of vegetation change in scenic areas can guide the configuration of tourism facilities and the formulation of vegetation protection measures.High spatial resolution remote sensing images can be used to detect subtle vegetation changes.The major objective of this study was to map and quantify forest vegetation changes in a national scenic location,the Purple Mountains of Nanjing,China,using multi-temporal cross-sensor high spatial resolution satellite images to identify the main drivers of the vegetation changes and provide a reference for sustainable management.We used Quickbird images acquired in 2004,IKONOS images acquired in 2009,and WorldView2 images acquired in 2015.Four pixel-based direct change detection methods including the normalized difference vegetation index difference method,multi-index integrated change analysis(MIICA),principal component analysis,and spectral gradient difference analysis were compared in terms of their change detection performances.Subsequently,the best pixel-based detection method in conjunction with object-oriented image analysis was used to extract subtle forest vegetation changes.An accuracy assessment using the stratified random sampling points was conducted to evaluate the performance of the change detection results.The results showed that the MIICA method was the best pixel-based change detection method.And the object-oriented MIICA with an overall accuracy of 0.907 and a kappa coefficient of 0.846 was superior to the pixel-based MIICA.From 2004 to 2009,areas of vegetation gain mainly occurred around the periphery of the study area,while areas of vegetation loss were observed in the interior and along the boundary of the study area due to construction activities,which contributed to 79%of the total area of vegetation loss.During 2009–2015,the greening initiatives around the construction areas increased the forest vegetation coverage,accounting for 84%of the total area of vegetation gain.In spite of this,vegetation loss occurred in the interior of the Purple Mountains due to infrastructure development that caused conversion from vegetation to impervious areas.We recommend that:(1)a local multi-agency team inspect and assess law enforcement regarding natural resource utilization;and(2)strengthen environmental awareness education.展开更多
Light-field imaging has wide applications in various domains,including microscale life science imaging,mesoscale neuroimaging,and macroscale fluid dynamics imaging.The development of deep learning-based reconstruction...Light-field imaging has wide applications in various domains,including microscale life science imaging,mesoscale neuroimaging,and macroscale fluid dynamics imaging.The development of deep learning-based reconstruction methods has greatly facilitated high-resolution light-field image processing,however,current deep learning-based light-field reconstruction methods have predominantly concentrated on the microscale.Considering the multiscale imaging capacity of light-field technique,a network that can work over variant scales of light-field image reconstruction will significantly benefit the development of volumetric imaging.Unfortunately,to our knowledge,no one has reported a universal high-resolution light-field image reconstruction algorithm that is compatible with microscale,mesoscale,and macroscale.To fill this gap,we present a real-time and universal network(RTU-Net)to reconstruct high-resolution light-field images at any scale.RTU-Net,as the first network that works over multiscale light-field image reconstruction,employs an adaptive loss function based on generative adversarial theory and consequently exhibits strong generalization capability.We comprehensively assessed the performance of RTU-Net through the reconstruction of multiscale light-field images,including microscale tubulin and mitochondrion dataset,mesoscale synthetic mouse neuro dataset,and macroscale light-field particle imaging velocimetry dataset.The results indicated that RTU-Net has achieved real-time and high-resolution light-field image reconstruction for volume sizes ranging from 300μm×300μm×12μm to 25 mm×25 mm×25 mm,and demonstrated higher resolution when compared with recently reported light-field reconstruction networks.The high-resolution,strong robustness,high efficiency,and especially the general applicability of RTU-Net will significantly deepen our insight into high-resolution and volumetric imaging.展开更多
Spectral imaging—a suite of techniques combining image acquisition with extremely high color resolution—plays an ever-increasing role in many fields,such as biomedicine,agriculture,geology,archeology,and environment...Spectral imaging—a suite of techniques combining image acquisition with extremely high color resolution—plays an ever-increasing role in many fields,such as biomedicine,agriculture,geology,archeology,and environmental control.^(1-3)The capability of visualizing,in real time,a tissue or terrain with spatially resolved chemical sensitivity can literally mean the difference between life and death.To appreciate the significance,consider how in vivo spectroscopic sensing of malignant tissue empowers the surgeon to minimize collateral damage during tumor removal while keeping the risk of cancer recurrence low.展开更多
[ Objective] The study aimed to improve methods of monitoring Karst Rocky Desertification （KRD） control projects and increase the working efficiency. [Method] Based on remote sensing images with medium and high spat...[ Objective] The study aimed to improve methods of monitoring Karst Rocky Desertification （KRD） control projects and increase the working efficiency. [Method] Based on remote sensing images with medium and high spatial resolution, KRD control projects in Disi River basin in Puan County were monitored, that is, information of the project construction in the study area was extracted using supervised classification and hu- man-computer interactive interpretation, and the monitoring results were testified with the aid of GPS. [Result] It was feasible to monitor KRD con- trol projects in Disi River basin based on remote sensing images with medium and high resolution, and the monitoring accuracy was satisfactory, reaching above 80% or 90%, so the method is worthy of popularizing. [ Conclusion] Remote sensing images with medium and high resolution can be used to monitor other KRD control Droiects.展开更多
Calman filtering method based on wavelet transform has been successfully applied to signal denoising. According to the different application methods and the realization forms of Calman filter, combined with the struct...Calman filtering method based on wavelet transform has been successfully applied to signal denoising. According to the different application methods and the realization forms of Calman filter, combined with the structural analysis of wavelet decomposition, we present kinds of multi-scale filtering methods into the category of the three. The simulation results show that the multi-scale Calman filtering method based on system layer has better performance. Synthetic aperture radar （SAR） images have rich texture information, which can reflect the spatial structure of objects. The texture feature is widely used in SAR image classification and SAR image segmentation. Affected by imaging factors, the direct use of texture features extracted from SAR images is not good enough. In order to avoid the traditional method of filtering followed the texture feature extraction caused by the loss of texture and edge information, this paper presents a texture feature extraction of SAR image, then using Robust PCA method, finally using texture feature clustering method K-means test after treatment with RPCA expression.展开更多
Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilizatio...Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.展开更多
In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can...In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can provide a more reliable approach in these situations.Current popular approaches mainly adopt the classification-based class activation maps(CAM)as initial pseudo labels to solve the task.展开更多
Based on the measurement model of inverse synthetic aperture radar (ISAR) within a small aspect sector,an imaging method was presented with the application of sparse signal processing.This method can form higher resol...Based on the measurement model of inverse synthetic aperture radar (ISAR) within a small aspect sector,an imaging method was presented with the application of sparse signal processing.This method can form higher resolution inverse synthetic aperture radar images from compensating incomplete measured data,and improves the clarity of the images and makes the feature structure much more clear,which is helpful for target recognition.The simulation results indicate that this method can provide clear ISAR images with high contrast under complex motion case.展开更多
Electromagnetic metasurfaces exhibit considerable potential for generating high-purity vortex beams and enabling high-resolution imaging and information encryption.However,traditional GHz devices face challenges,inclu...Electromagnetic metasurfaces exhibit considerable potential for generating high-purity vortex beams and enabling high-resolution imaging and information encryption.However,traditional GHz devices face challenges,including reduced efficiency due to bulky size and material losses.Herein,we designed a multilayer structure and demonstrated through simulations that this configuration served as an efficient transmissive meta-atom.We designed arrays in multiple sizes and finally determined that the optimal minimal unit was the meta-quaternion vortex array,which was subsequently used as the pixel basis for the target image.A digitally patterned GHz metadevice was fabricated and experimentally characterized with right-handed circularly polarized(RCP)light.The experimental results were in excellent agreement with the simulations.We combined the classical nine-grid encryption method(Luoshu)with metasurfaces and introduced the weighted superposition computation technique(WeightLock)to achieve multilayer encryption of target characters.Our research offered novel strategies for the next-generation 5G/6G communication systems,radar detection,and information encryption fields,demonstrating broad application prospects in intelligent communication and advanced radar technologies.展开更多
Background：There are few studies for evaluating wall characteristics of intracranial vertebral artery hypoplasia （VAH）.The aim of this study was to determine wall characteristics of VAH with three-dimensional volum...Background：There are few studies for evaluating wall characteristics of intracranial vertebral artery hypoplasia （VAH）.The aim of this study was to determine wall characteristics of VAH with three-dimensional volumetric isotropic turbo spin echo acquisition （3D VISTA） images and differentiate between acquired atherosclerotic stenosis and VAH.Methods：Thirty patients with suspicious VAH by luminograms were retrospectively enrolled between January 2014 and February 2015.The patients were classified as ＂acquired atherosclerotic stenosis＂ or ＂VAH＂ based on 3D VISTA images.The wall characteristics of VAH were assessed to determine the presence of atherosclerotic lesions,and the patients were classified into two subgroups （VAH with atherosclerosis and VAH with normal wall）.Wall characteristics of basilar arteries and vertebral arteries were also assessed.The clinical and wall characteristics were compared between the two groups.Results：Five of 30 patients with suspicious VAH were finally diagnosed as acquired atherosclerotic stenosis by 3D VISTA images.25 patients were finally diagnosed as VAH including 16 （64.00%） patients with atherosclerosis and 9 （36.00%） patients with normal wall.In the 16 patients with atherosclerosis,plaque was found in 9 patients,slight wall thickening in 6 patients,and thrombus and wall thickening in 1 patient.Compared with VAH patients with normal wall,VAH patients with atherosclerosis showed atherosclerotic basilar arteries and dominant vertebral arteries more frequently （P =0.000）.Conclusions：Three-dimensional VISTA images enable differentiation between the acquired atherosclerotic stenosis and VAH.VAH was also prone to atherosclerotic processes.展开更多
To ensure project safety and secure public support, an integrated and comprehensive monitoring program is needed within a carbon capture and storage(CCS) project. Monitoring can be done using many well-established tec...To ensure project safety and secure public support, an integrated and comprehensive monitoring program is needed within a carbon capture and storage(CCS) project. Monitoring can be done using many well-established techniques from various fields, and the seismic method proves to be the crucial one. This method is widely used to determine the CO_(2) distribution, image the plume development, and quantitatively estimate the concentration. Because both the CO_(2) distribution and the potential migration pathway can be spatially small scale, high resolution for seismic imaging is demanded. However, obtaining a high-resolution image of a subsurface structure in marine settings is difficult. Herein, we introduce the novel Hcable(Harrow-like cable system) technique, which may be applied to offshore CCS monitoring. This technique uses a highfrequency source(the dominant frequency>100 Hz) to generate seismic waves and a combination of a long cable and several short streamers to receive seismic waves. Ultrahigh-frequency seismic images are achieved through the processing of Hcable seismic data. Hcable is then applied in a case study to demonstrate its detailed characterization for small-scale structures. This work reveals that Hcable is a promising tool for timelapse seismic monitoring of oceanic CCS.展开更多
While metal materials historically have served as permanent implants and were designed to avoid degradation,next generation bioabsorbable metals for medical devices such as vascular stents are under development,which ...While metal materials historically have served as permanent implants and were designed to avoid degradation,next generation bioabsorbable metals for medical devices such as vascular stents are under development,which would elute metal ions and corrosion byproducts into tissues.The fate of these eluted products and their local distribution in vascular tissue largely under studied.In this study,we employ a high spatial resolution spectrometric imaging modality,laser ablation inductively coupled plasma time-of-flight mass spectrometry(LA-ICP-TOF-MS)to map the metal distribution,(herein refered to as laser ablation mapping,or LAM)from Mg alloys within the mouse vascular system and approximate their local concentrations.We used a novel rare earth element bearing Mg alloy(WE22)wire implanted within the abdominal aorta of transgenic hypercholesterolemic mice(APOE/)to simulate a bioabsorbable vascular prosthesis for up to 30 days.We describe qualitatively and semi-quantitatively implant-derived corrosion product presence throughout the tissue cross sections,and their approximate concentrations within the various vessel structures.Additionally,we report the spatial changes of corrosion products,which we postulate are mediated by phagocytic inflammatory cells such as macrophages(MΦ’s).展开更多
基金Supported by the Key Research and Development Plan of Shaanxi Province,No.2021SF-298.
文摘BACKGROUND Neurovascular compression(NVC) is the main cause of primary trigeminal neuralgia(TN) and hemifacial spasm(HFS). Microvascular decompression(MVD) is an effective surgical method for the treatment of TN and HFS caused by NVC. The judgement of NVC is a critical step in the preoperative evaluation of MVD, which is related to the effect of MVD treatment. Magnetic resonance imaging(MRI) technology has been used to detect NVC prior to MVD for several years. Among many MRI sequences, three-dimensional time-of-flight magnetic resonance angiography(3D TOF MRA) is the most widely used. However, 3D TOF MRA has some shortcomings in detecting NVC. Therefore, 3D TOF MRA combined with high resolution T2-weighted imaging(HR T2WI) is considered to be a more effective method to detect NVC.AIM To determine the value of 3D TOF MRA combined with HR T2WI in the judgment of NVC, and thus to assess its value in the preoperative evaluation of MVD.METHODS Related studies published from inception to September 2022 based on PubMed, Embase, Web of Science, and the Cochrane Library were retrieved. Studies that investigated 3D TOF MRA combined with HR T2WI to judge NVC in patients with TN or HFS were included according to the inclusion criteria. Studies without complete data or not relevant to the research topics were excluded. The Quality Assessment of Diagnostic Accuracy Studies checklist was used to assess the quality of included studies. The publication bias of the included literature was examined by Deeks’ test. An exact binomial rendition of the bivariate mixed-effects regression model was used to synthesize data. Data analysis was performed using the MIDAS module of statistical software Stata 16.0. Two independent investigators extracted patient and study characteristics, and discrepancies were resolved by consensus. Individual and pooled sensitivities and specificities were calculated. The I_(2) statistic and Q test were used to test heterogeneity. The study was registered on the website of PROSERO(registration No. CRD42022357158).RESULTS Our search identified 595 articles, of which 12(including 855 patients) fulfilled the inclusion criteria. Bivariate analysis showed that the pooled sensitivity and specificity of 3D TOF MRA combined with HR T2WI for detecting NVC were 0.96 [95% confidence interval(CI): 0.92-0.98] and 0.92(95%CI: 0.74-0.98), respectively. The pooled positive likelihood ratio was 12.4(95%CI: 3.2-47.8), pooled negative likelihood ratio was 0.04(95%CI: 0.02-0.09), and pooled diagnostic odds ratio was 283(95%CI: 50-1620). The area under the receiver operating characteristic curve was 0.98(95%CI: 0.97-0.99). The studies showed no substantial heterogeneity(I2 = 0, Q = 0.001 P = 0.50).CONCLUSION Our results suggest that 3D TOF MRA combined with HR T2WI has excellent sensitivity and specificity for judging NVC in patients with TN or HFS. This method can be used as an effective tool for preoperative evaluation of MVD.
基金supported by the National Natural Science Foundation of China[grant number 41801390]the National Key R&D Program of China[grant number 2018YFD1100405].
文摘In many cases,the Digital Surface Models(DSMs)and Digital Elevation Models(DEMs)are obtained with Light Detection and Ranging(LiDAR)or stereo matching.As an active method,LiDAR is very accurate but expensive,thus often limiting its use in small-scale acquisition.Stereo matching is suitable for large-scale acquisition of terrain information as the increase of satellite stereo sensors.However,underperformance of stereo matching easily occurs in textureless areas.Accordingly,this study proposed a Shading Aware DSM GEneration Method(SADGE)with high resolution multi-view satellite images.Considering the complementarity of stereo matching and Shape from Shading(SfS),SADGE combines the advantage of stereo matching and SfS technique.First,an improved Semi-Global Matching(SGM)technique is used to generate an initial surface expressed by a DSM;then,it is refined by optimizing the objective function which modeled the imaging process with the illumination,surface albedo,and normal object surface.Different from the existing shading-based DEM refinement or generation method,no information about the illumination or the viewing angle is needed while concave/convex ambiguity can be avoided as multi-view images are utilized.Experiments with ZiYuan-3 and GaoFen-7 images show that the proposed method can generate higher accuracy DSM(12.5-56.3%improvement)with sound overall shape and temporarily detailed surface compared with a software solution(SURE)for multi-view stereo.
基金supported by the Chinese Academy of Sciences Project for Young Scientists in Basic Research(YSBR067)the Natural Science Foundation of Jiangsu Province(BK20240024)the Youth Innovation Promotion Association of the Chinese Academy of Sciences(Y2023087)。
文摘Mesoscopy refers to imaging methodologies that provide a field of view(FOV)ranging from several millimeters to centimeters while achieving cellular or even subcellular resolution(Figure 1).This technological framework employs specially designed large-scale objective lenses to correct aberrations across extended FOVs,synchronized with light-field acquisition modalities through either scanning point detection or large-format array detection.Conventional microscopes,constrained by the limitations of objective lenses,exhibit a trade-off between the FOV and resolution.To achieve both high resolution and a large FOV,common approaches such as FOV stitching and Fourier ptychography were employed.However,these methods were extremely slow and imposed numerous constraints on samples.In 2016,a mesoscopic objective lens was introduced to address these challenges,achieving a 6 mm FOV and 0.7 mm resolution,thereby increasing the imaging throughput of conventional objective lenses by orders of magnitude.1 In the same year,this technology was recognized as one of the top ten physics breakthroughs worldwide by Physics World.Since then,mesoscopic imaging technology has gradually gained momentum and has been applied in various fields.
文摘Introduction of the stepwise phase dispersion compensation layer allowed broadband achromatic metalens to have a high numerical aperture,which enabled high-resolution metalens imaging.
基金National Natural Science Foundation of China(No.41871305)National Key Research and Development Program of China(No.2017YFC0602204)+2 种基金Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(No.CUGQY1945)Open Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education and the Fundamental Research Funds for the Central Universities(No.GLAB2019ZR02)Open Fund of Laboratory of Urban Land Resources Monitoring and Simulation,Ministry of Natural Resources,China(No.KF-2020-05-068)。
文摘The exploration of building detection plays an important role in urban planning,smart city and military.Aiming at the problem of high overlapping ratio of detection frames for dense building detection in high resolution remote sensing images,we present an effective YOLOv3 framework,corner regression-based YOLOv3(Correg-YOLOv3),to localize dense building accurately.This improved YOLOv3 algorithm establishes a vertex regression mechanism and an additional loss item about building vertex offsets relative to the center point of bounding box.By extending output dimensions,the trained model is able to output the rectangular bounding boxes and the building vertices meanwhile.Finally,we evaluate the performance of the Correg-YOLOv3 on our self-produced data set and provide a comparative analysis qualitatively and quantitatively.The experimental results achieve high performance in precision(96.45%),recall rate(95.75%),F1 score(96.10%)and average precision(98.05%),which were 2.73%,5.4%,4.1%and 4.73%higher than that of YOLOv3.Therefore,our proposed algorithm effectively tackles the problem of dense building detection in high resolution images.
文摘Road extraction plays an important role in many applications such as car navigation, but the manual extraction of roads is a laborious, tedious task. To speed the extraction of roads, an approach based on particle filtering to extract automatically roads from high resolution imagery is proposed. Particle filtering provides a statistical framework for propagating sample-based approximations of posterior distributions and has almost no restriction on the ingredients of the model. We integrate the similarity of grey value and the edge point distribution of roads into particle filtering to deal with complex scenes. To handle road appearance changes the tracking algorithm is allowed to update the road model during temporally stable image observations. A fully automatic initialization strategy is used. Experimental results show that the proposed approach is a promising and fully automatic method for extracting roads from images, even in the presence of occlusions.
基金the National Science Fund for Distinguished Young Scholars of China (No. 51625501)the Aeronautical Science Foundation of China (No. 201946051002)
文摘Small-object detection has long been a challenge.High-megapixel cameras are used to solve this problem in industries.However,current detectors are inefficient for high-resolution images.In this work,we propose a new module called Pre-Locate Net,which is a plug-and-play structure that can be combined with most popular detectors.We inspire the use of classification ideas to obtain candidate regions in images,greatly reducing the amount of calculation,and thus achieving rapid detection in high-resolution images.Pre-Locate Net mainly includes two parts,candidate region classification and behavior classification.Candidate region classification is used to obtain a candidate region,and behavior classification is used to estimate the scale of an object.Different follow-up processing is adopted according to different scales to balance the variance of the network input.Different from the popular candidate region generation method,we abandon the idea of regression of a bounding box and adopt the concept of classification,so as to realize the prediction of a candidate region in the shallow network.We build a high-resolution dataset of aircraft and landing gears covering complex scenes to verify the effectiveness of our method.Compared to state-of-the-art detectors(e.g.,Guided Anchoring,Libra-RCNN,and FASF),our method achieves the best m AP of 94.5 on 1920×1080 images at 16.7 FPS.
文摘The dispersoid phase Al_(20)Cu_2Mn_3 in a 2024 Al alloy is commonly composed of twins,An ob- servation of corresponding high resolution image shows that the twin boundary plane is a glide plane other than mirror one.Two neighbouring components of twins are not symmetry of re- flection or rotation,but of glide reflection.The“diamond”glide plane is(101)and the glide vector is(1/4)(-).Components of twins in the phase take shape of prism with the longitudinal edge being parallel to[010]and side faces being{101}and{100}.
基金supported by the National Natural Science Foundation of China(31670552)the PAPD(Priority Academic Program Development)of Jiangsu provincial universities and the China Postdoctoral Science Foundation funded projectthis work was performed while the corresponding author acted as an awardee of the 2017 Qinglan Project sponsored by Jiangsu Province。
文摘Accurate information on the location and magnitude of vegetation change in scenic areas can guide the configuration of tourism facilities and the formulation of vegetation protection measures.High spatial resolution remote sensing images can be used to detect subtle vegetation changes.The major objective of this study was to map and quantify forest vegetation changes in a national scenic location,the Purple Mountains of Nanjing,China,using multi-temporal cross-sensor high spatial resolution satellite images to identify the main drivers of the vegetation changes and provide a reference for sustainable management.We used Quickbird images acquired in 2004,IKONOS images acquired in 2009,and WorldView2 images acquired in 2015.Four pixel-based direct change detection methods including the normalized difference vegetation index difference method,multi-index integrated change analysis(MIICA),principal component analysis,and spectral gradient difference analysis were compared in terms of their change detection performances.Subsequently,the best pixel-based detection method in conjunction with object-oriented image analysis was used to extract subtle forest vegetation changes.An accuracy assessment using the stratified random sampling points was conducted to evaluate the performance of the change detection results.The results showed that the MIICA method was the best pixel-based change detection method.And the object-oriented MIICA with an overall accuracy of 0.907 and a kappa coefficient of 0.846 was superior to the pixel-based MIICA.From 2004 to 2009,areas of vegetation gain mainly occurred around the periphery of the study area,while areas of vegetation loss were observed in the interior and along the boundary of the study area due to construction activities,which contributed to 79%of the total area of vegetation loss.During 2009–2015,the greening initiatives around the construction areas increased the forest vegetation coverage,accounting for 84%of the total area of vegetation gain.In spite of this,vegetation loss occurred in the interior of the Purple Mountains due to infrastructure development that caused conversion from vegetation to impervious areas.We recommend that:(1)a local multi-agency team inspect and assess law enforcement regarding natural resource utilization;and(2)strengthen environmental awareness education.
基金supported by National Natural Science Foundation of China(12402336,82201637,U20A2070,and 12025202)National High-Level Talent Project(YQR23069)+6 种基金Natural Science Foundation of Jiangsu Province(BK20230876)the Young Elite Scientist Sponsorship Program by CAST(YESS20210238)Forwardlooking layout projects(1002-ILB24009)Zhejang Provincial Medical and Health Technology Project(Grant No.2024KY246,2025KY180)Scientific Research Foundation of Hangzhou City University(No.J-202402)Open Research Fund of the State Key Laboratory of Brain-Machine Intelligence,Zhejiang University(Grant No.BMI2400025)Hangzhou Science and Technology Bureau.
文摘Light-field imaging has wide applications in various domains,including microscale life science imaging,mesoscale neuroimaging,and macroscale fluid dynamics imaging.The development of deep learning-based reconstruction methods has greatly facilitated high-resolution light-field image processing,however,current deep learning-based light-field reconstruction methods have predominantly concentrated on the microscale.Considering the multiscale imaging capacity of light-field technique,a network that can work over variant scales of light-field image reconstruction will significantly benefit the development of volumetric imaging.Unfortunately,to our knowledge,no one has reported a universal high-resolution light-field image reconstruction algorithm that is compatible with microscale,mesoscale,and macroscale.To fill this gap,we present a real-time and universal network(RTU-Net)to reconstruct high-resolution light-field images at any scale.RTU-Net,as the first network that works over multiscale light-field image reconstruction,employs an adaptive loss function based on generative adversarial theory and consequently exhibits strong generalization capability.We comprehensively assessed the performance of RTU-Net through the reconstruction of multiscale light-field images,including microscale tubulin and mitochondrion dataset,mesoscale synthetic mouse neuro dataset,and macroscale light-field particle imaging velocimetry dataset.The results indicated that RTU-Net has achieved real-time and high-resolution light-field image reconstruction for volume sizes ranging from 300μm×300μm×12μm to 25 mm×25 mm×25 mm,and demonstrated higher resolution when compared with recently reported light-field reconstruction networks.The high-resolution,strong robustness,high efficiency,and especially the general applicability of RTU-Net will significantly deepen our insight into high-resolution and volumetric imaging.
文摘Spectral imaging—a suite of techniques combining image acquisition with extremely high color resolution—plays an ever-increasing role in many fields,such as biomedicine,agriculture,geology,archeology,and environmental control.^(1-3)The capability of visualizing,in real time,a tissue or terrain with spatially resolved chemical sensitivity can literally mean the difference between life and death.To appreciate the significance,consider how in vivo spectroscopic sensing of malignant tissue empowers the surgeon to minimize collateral damage during tumor removal while keeping the risk of cancer recurrence low.
基金Supported by the Key Science and Technology Projects of Guizhou Province,China[(2007)3017,(2008)3022]Major Special Project of Guizhou Province,China(2006-6006-2)
文摘[ Objective] The study aimed to improve methods of monitoring Karst Rocky Desertification （KRD） control projects and increase the working efficiency. [Method] Based on remote sensing images with medium and high spatial resolution, KRD control projects in Disi River basin in Puan County were monitored, that is, information of the project construction in the study area was extracted using supervised classification and hu- man-computer interactive interpretation, and the monitoring results were testified with the aid of GPS. [Result] It was feasible to monitor KRD con- trol projects in Disi River basin based on remote sensing images with medium and high resolution, and the monitoring accuracy was satisfactory, reaching above 80% or 90%, so the method is worthy of popularizing. [ Conclusion] Remote sensing images with medium and high resolution can be used to monitor other KRD control Droiects.
文摘Calman filtering method based on wavelet transform has been successfully applied to signal denoising. According to the different application methods and the realization forms of Calman filter, combined with the structural analysis of wavelet decomposition, we present kinds of multi-scale filtering methods into the category of the three. The simulation results show that the multi-scale Calman filtering method based on system layer has better performance. Synthetic aperture radar （SAR） images have rich texture information, which can reflect the spatial structure of objects. The texture feature is widely used in SAR image classification and SAR image segmentation. Affected by imaging factors, the direct use of texture features extracted from SAR images is not good enough. In order to avoid the traditional method of filtering followed the texture feature extraction caused by the loss of texture and edge information, this paper presents a texture feature extraction of SAR image, then using Robust PCA method, finally using texture feature clustering method K-means test after treatment with RPCA expression.
文摘Global motion estimation (GME) algorithms are widely applied to computer vision and video processing. In the previous works, the image resolutions are usually low for the real-time requirement (e.g. video stabilization). However, in some mobile devices applications (e.g. image sequence panoramic stitching), the high resolution is necessary to obtain satisfactory quality of panoramic image. However, the computational cost will become too expensive to be suitable for the low power consumption requirement of mobile device. The full search algorithm can obtain the global minimum with extremely computational cost, while the typical fast algorithms may suffer from the local minimum problem. This paper proposed a fast algorithm to deal with 2560 × 1920 high-resolution (HR) image sequences. The proposed method estimates the motion vector by a two-level coarse-to-fine scheme which only exploits sparse reference blocks (25 blocks in this paper) in each level to determine the global motion vector, thus the computational costs are significantly decreased. In order to increase the effective search range and robustness, the predictive motion vector (PMV) technique is used in this work. By the comparisons of computational complexity, the proposed algorithm costs less addition operations than the typical Three-Step Search algorithm (TSS) for estimating the global motion of the HR images without the local minimum problem. The quantitative evaluations show that our method is comparable to the full search algorithm (FSA) which is considered to be the golden baseline.
文摘In the field of optoelectronics,certain types of data may be difficult to accurately annotate,such as high-resolution optoelectronic imaging or imaging in certain special spectral ranges.Weakly supervised learning can provide a more reliable approach in these situations.Current popular approaches mainly adopt the classification-based class activation maps(CAM)as initial pseudo labels to solve the task.
基金Project supported by the National Natural Science Foundation of China
文摘Based on the measurement model of inverse synthetic aperture radar (ISAR) within a small aspect sector,an imaging method was presented with the application of sparse signal processing.This method can form higher resolution inverse synthetic aperture radar images from compensating incomplete measured data,and improves the clarity of the images and makes the feature structure much more clear,which is helpful for target recognition.The simulation results indicate that this method can provide clear ISAR images with high contrast under complex motion case.
基金National Key Research and Development Program of China(2024YFE107800)National Natural Science Foundation of China(62205127)+1 种基金Basic Research Program of Jiangsu(BK20231493)Key Laboratory of Advanced Optical Manufacturing Technologies of Jiangsu Province(KJS2272)。
文摘Electromagnetic metasurfaces exhibit considerable potential for generating high-purity vortex beams and enabling high-resolution imaging and information encryption.However,traditional GHz devices face challenges,including reduced efficiency due to bulky size and material losses.Herein,we designed a multilayer structure and demonstrated through simulations that this configuration served as an efficient transmissive meta-atom.We designed arrays in multiple sizes and finally determined that the optimal minimal unit was the meta-quaternion vortex array,which was subsequently used as the pixel basis for the target image.A digitally patterned GHz metadevice was fabricated and experimentally characterized with right-handed circularly polarized(RCP)light.The experimental results were in excellent agreement with the simulations.We combined the classical nine-grid encryption method(Luoshu)with metasurfaces and introduced the weighted superposition computation technique(WeightLock)to achieve multilayer encryption of target characters.Our research offered novel strategies for the next-generation 5G/6G communication systems,radar detection,and information encryption fields,demonstrating broad application prospects in intelligent communication and advanced radar technologies.
基金Source of Support： This study was supported by grants from China Postdoctoral Science Foundation （No. 2014M562633）, China-Japan Friendship Hospital Youth Science and Technology Excellence Project （No. 2014-QNYC-A-04）, National Natural Science Foundation of China （No. 81173595, 30670731, 81070925, and 81471767）, and National Basic Research Program （973 Program） of China （No. 2013CB733805）.
文摘Background：There are few studies for evaluating wall characteristics of intracranial vertebral artery hypoplasia （VAH）.The aim of this study was to determine wall characteristics of VAH with three-dimensional volumetric isotropic turbo spin echo acquisition （3D VISTA） images and differentiate between acquired atherosclerotic stenosis and VAH.Methods：Thirty patients with suspicious VAH by luminograms were retrospectively enrolled between January 2014 and February 2015.The patients were classified as ＂acquired atherosclerotic stenosis＂ or ＂VAH＂ based on 3D VISTA images.The wall characteristics of VAH were assessed to determine the presence of atherosclerotic lesions,and the patients were classified into two subgroups （VAH with atherosclerosis and VAH with normal wall）.Wall characteristics of basilar arteries and vertebral arteries were also assessed.The clinical and wall characteristics were compared between the two groups.Results：Five of 30 patients with suspicious VAH were finally diagnosed as acquired atherosclerotic stenosis by 3D VISTA images.25 patients were finally diagnosed as VAH including 16 （64.00%） patients with atherosclerosis and 9 （36.00%） patients with normal wall.In the 16 patients with atherosclerosis,plaque was found in 9 patients,slight wall thickening in 6 patients,and thrombus and wall thickening in 1 patient.Compared with VAH patients with normal wall,VAH patients with atherosclerosis showed atherosclerotic basilar arteries and dominant vertebral arteries more frequently （P =0.000）.Conclusions：Three-dimensional VISTA images enable differentiation between the acquired atherosclerotic stenosis and VAH.VAH was also prone to atherosclerotic processes.
基金Supported by the project of Sanya Yazhou Bay Science and Technology City (Grant No:SCKJ-JYRC-2022-14)。
文摘To ensure project safety and secure public support, an integrated and comprehensive monitoring program is needed within a carbon capture and storage(CCS) project. Monitoring can be done using many well-established techniques from various fields, and the seismic method proves to be the crucial one. This method is widely used to determine the CO_(2) distribution, image the plume development, and quantitatively estimate the concentration. Because both the CO_(2) distribution and the potential migration pathway can be spatially small scale, high resolution for seismic imaging is demanded. However, obtaining a high-resolution image of a subsurface structure in marine settings is difficult. Herein, we introduce the novel Hcable(Harrow-like cable system) technique, which may be applied to offshore CCS monitoring. This technique uses a highfrequency source(the dominant frequency>100 Hz) to generate seismic waves and a combination of a long cable and several short streamers to receive seismic waves. Ultrahigh-frequency seismic images are achieved through the processing of Hcable seismic data. Hcable is then applied in a case study to demonstrate its detailed characterization for small-scale structures. This work reveals that Hcable is a promising tool for timelapse seismic monitoring of oceanic CCS.
基金under Grant P41 GM135018(as well as Grant S10OD026786)from the National Institute of General Medical Sciences of the National Institutes of Healthpartially supported by the National Heart Blood Lung Institute under the award numbers R15HL167221-01 and R15HL167221-02(RJG).
文摘While metal materials historically have served as permanent implants and were designed to avoid degradation,next generation bioabsorbable metals for medical devices such as vascular stents are under development,which would elute metal ions and corrosion byproducts into tissues.The fate of these eluted products and their local distribution in vascular tissue largely under studied.In this study,we employ a high spatial resolution spectrometric imaging modality,laser ablation inductively coupled plasma time-of-flight mass spectrometry(LA-ICP-TOF-MS)to map the metal distribution,(herein refered to as laser ablation mapping,or LAM)from Mg alloys within the mouse vascular system and approximate their local concentrations.We used a novel rare earth element bearing Mg alloy(WE22)wire implanted within the abdominal aorta of transgenic hypercholesterolemic mice(APOE/)to simulate a bioabsorbable vascular prosthesis for up to 30 days.We describe qualitatively and semi-quantitatively implant-derived corrosion product presence throughout the tissue cross sections,and their approximate concentrations within the various vessel structures.Additionally,we report the spatial changes of corrosion products,which we postulate are mediated by phagocytic inflammatory cells such as macrophages(MΦ’s).
