The most common methods for three-dimensional reconstruction of peripheral nerve fascicles include histological and radiology techniques. Histological techniques have many drawbacks including an enormous manual worklo...The most common methods for three-dimensional reconstruction of peripheral nerve fascicles include histological and radiology techniques. Histological techniques have many drawbacks including an enormous manual workload and poor image registration. Micro-magnetic resonance imaging（Micro-MRI）, an emerging radiology technique, has been used to report results in the brain, liver and tumor tissues. However, micro-MRI usage for obtaining intraneural structures has not been reported. The aim of this study was to present a new imaging method for three-dimensional reconstruction of peripheral nerve fascicles by ~1T micro-MRI. Freshly harvested sciatic nerve samples from an amputated limb were divided into four groups. Two different scanning conditions（Mannerist Solution/GD-DTPA contrast agent, distilled water） were selected, and both T1 and T2 phases programmed for each scanning condition. Three clinical surgeons evaluated the quality of the images via a standardized scale. Moreover, to analyze deformation of the two-dimensional image, the nerve diameter and total area of the micro-MRI images were compared after hematoxylin-eosin staining. The results show that rapid micro-MRI imaging method can be used for three-dimensional reconstruction of the fascicle structure. Nerve sample immersed in contrast agent（Mannerist Solution/GD-DTPA） and scanned in the T1 phase was the best. Moreover, the nerve sample was scanned freshly and can be recycled for other procedures. MRI images show better stability and smaller deformation compared with histological images. In conclusion, micro-MRI provides a feasible and rapid method for three-dimensional reconstruction of peripheral nerve fascicles, which can clearly show the internal structure of the peripheral nerve.展开更多
A novel and fast three-dimensional reconstruction method for a Compton camera and its performance in radionuclide imaging is proposed and analyzed in this study. The conical surface sampling back-projection method wit...A novel and fast three-dimensional reconstruction method for a Compton camera and its performance in radionuclide imaging is proposed and analyzed in this study. The conical surface sampling back-projection method with scattering angle correction(CSS-BP-SC) can quickly perform the back-projection process of the Compton cone and can be used to precompute the list-mode maximum likelihood expectation maximization(LM-MLEM). A dedicated parallel architecture was designed for the graphics processing unit acceleration of the back-projection and iteration stage of the CSS-BP-SC-based LM-MLEM. The imaging results of the two-point source Monte Carlo(MC) simulation demonstrate that by analyzing the full width at half maximum along the three coordinate axes, the CSS-BP-SC-based LM-MLEM can obtain imaging results comparable to those of the traditional reconstruction algorithm, that is, the simple back-projection-based LM-MLEM. The imaging results of the mouse phantom MC simulation and experiment demonstrate that the reconstruction results obtained by the proposed method sufficiently coincide with the set radioactivity distribution, and the speed increased by more than 664 times compared to the traditional reconstruction algorithm in the mouse phantom experiment. The proposed method will further advance the imaging applications of Compton cameras.展开更多
Existing three-dimensional(3D) imaging technologies have issues such as requiring active illumination, multiple exposures, or coding modulation. We propose a passive single 3D imaging method based on an ordinary imagi...Existing three-dimensional(3D) imaging technologies have issues such as requiring active illumination, multiple exposures, or coding modulation. We propose a passive single 3D imaging method based on an ordinary imaging system.Using the point spread function of the imaging system to realize the non-coding measurement on the target, the full-focus images and depth information of the 3D target can be extracted from a single two-dimensional(2D) image through the compressed sensing algorithm. Simulation and experiments show that this approach can complete passive 3D imaging based on an ordinary imaging system without any coding operations. This method can achieve millimeter-level vertical resolution under single exposure conditions and has the potential for real-time dynamic 3D imaging. It improves the efficiency of 3D information detection, reduces the complexity of the imaging system, and may be of considerable value to the field of computer vision and other related applications.展开更多
In order to obtain a better sandstone three-dimensional （3D） reconstruction result which is more similar to the original sample, an algorithm based on stationarity for a two-dimensional （2D） training image is prop...In order to obtain a better sandstone three-dimensional （3D） reconstruction result which is more similar to the original sample, an algorithm based on stationarity for a two-dimensional （2D） training image is proposed. The second-order statistics based on texture features are analyzed to evaluate the scale stationarity of the training image. The multiple-point statistics of the training image are applied to obtain the multiple-point statistics stationarity estimation by the multi-point density function. The results show that the reconstructed 3D structures are closer to reality when the training image has better scale stationarity and multiple-point statistics stationarity by the indications of local percolation probability and two-point probability. Moreover, training images with higher multiple-point statistics stationarity and lower scale stationarity are likely to obtain closer results to the real 3D structure, and vice versa. Thus, stationarity analysis of the training image has far-reaching significance in choosing a better 2D thin section image for the 3D reconstruction of porous media. Especially, high-order statistics perform better than low-order statistics.展开更多
BACKGROUND Inguinal hernias are common after surgery.Tension-free repair is widely accepted as the main method for managing inguinal hernias.Adequate exposure,coverage,and repair of the myopectineal orifice(MPO)are ne...BACKGROUND Inguinal hernias are common after surgery.Tension-free repair is widely accepted as the main method for managing inguinal hernias.Adequate exposure,coverage,and repair of the myopectineal orifice(MPO)are necessary.However,due to differences in race and sex,people’s body shapes vary.According to European guidelines,the patch should measure 10 cm×15 cm.If any part of the MPO is dissected,injury to the nerves,vascular network,or organs may occur during surgery,thereby leading to inguinal discomfort,pain,and seroma formation after surgery.Therefore,accurate localization and measurement of the boundary of the MPO are crucial for selecting the optimal patch for inguinal hernia repair.AIM To compare the size of the MPO measured on three-dimensional multislice spiral computed tomography(CT)with that measured via laparoscopy and explore the relevant factors influencing the size of the MPO.METHODS Clinical data from 74 patients who underwent laparoscopic tension-free inguinal hernia repair at the General Surgery Department of the First Affiliated Hospital of Anhui University of Science and Technology between September 2022 and July 2024 were collected and analyzed retrospectively.Transabdominal preperitoneal was performed.Sixty-four males and 10 females,with an average age of 58.30±12.32 years,were included.The clinical data of the patients were collected.The boundary of the MPO was measured on three-dimensional CT images before surgery and then again during transabdominal preperitoneal.All the preoperative and intraoperative data were analyzed via paired t-tests.A t-test was used for comparisons of age,body mass index,and sex between the groups.In the comparative analysis,a P value less than 0.05 indicated a significant difference.RESULTS The boundaries of the MPO on 3-dimensional CT images measured 7.05±0.47 cm and 6.27±0.61 cm,and the area of the MPO was 19.54±3.33 cm^(2).The boundaries of the MPO during surgery were 7.18±0.51 cm and 6.17±0.40 cm.The errors were not statistically significant.However,the intraoperative BD(the width of the MPO,P=0.024,P<0.05)and preoperative AC(the length of the MPO,P=0.045,P<0.05)significantly differed according to sex.The AC and BD measurements before and during surgery were not significantly different according to age,body mass index,hernia side or hernia type(P>0.05).CONCLUSION The application of this technology can aid in determining the most appropriate dissection range and patch size.展开更多
BACKGROUND Percutaneous transhepatic biliary drainage(PTBD)is one of the primary clinical treatment options for patients with obstructive jaundice.In recent years,PTBD assisted by three-dimensional(3D)reconstruction t...BACKGROUND Percutaneous transhepatic biliary drainage(PTBD)is one of the primary clinical treatment options for patients with obstructive jaundice.In recent years,PTBD assisted by three-dimensional(3D)reconstruction technology has been widely implemented,but its advantages over traditional methods remains inconclusive.Thus,a discussion is warranted.AIM To explore the safety and efficacy of 3D reconstruction technology-assisted PTBD.METHODS We systematically searched the databases including the Cochrane Library,PubMed,EMBASE,Web of Science and China National Knowledge Infrastructure.The search period extended from the establishment of each database to November,2024.We screened the literature according to predefined inclusion and exclusion criteria,assessed the quality of the studies,and extracted data.Meta-analysis was performed using Revman 5.4.1 software.RESULTS A total of 15 studies were included,involving 1434 patients.The results of the meta-analysis showed that compared with the traditional group,the overall post-operative complications rate in the 3D reconstruction technology group was significantly lower[odds ratio=0.25;95%confidence interval(CI):0.17-0.36,P<0.00001].The overall puncture success rate in the 3D reconstruction group was better than those in the traditional group(odds ratio=3.61;95%CI:1.98-6.55,P<0.0001).However,there was no significant difference between the two groups in the reduction levels of postoperative total bilirubin(mean difference=-1.38;95%CI:-3.29 to 0.53,P=0.16).Subgroup analysis were conducted on the surgery time according to guidance stages of the 3D reconstruction,3D reconstruction imaging modalities,and types of studies.The results were stable,with no significant changes observed.CONCLUSION 3D reconstruction technology significantly improves the puncture success rate and safety of PTBD.However,it has no significant advantage in bile drainage effectiveness.Continued research is warranted to further explore its clinical value and optimize its application.展开更多
Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferome...Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferometric imaging faces the impact of multi-stage degradation. Most exsiting interferometric spectrum reconstruction methods are based on tradition model-based framework with multiple steps, showing poor efficiency and restricted performance. Thus, we propose an interferometric spectrum reconstruction method based on degradation synthesis and deep learning.Firstly, based on imaging mechanism, we proposed an mathematical model of interferometric imaging to analyse the degradation components as noises and trends during imaging. The model consists of three stages, namely instrument degradation, sensing degradation, and signal-independent degradation process. Then, we designed calibration-based method to estimate parameters in the model, of which the results are used for synthesizing realistic dataset for learning-based algorithms.In addition, we proposed a dual-stage interferogram spectrum reconstruction framework, which supports pre-training and integration of denoising DNNs. Experiments exhibits the reliability of our degradation model and synthesized data, and the effectiveness of the proposed reconstruction method.展开更多
BACKGROUND Deep learning-based super-resolution(SR)reconstruction can obtain high-quality images with more detailed information.AIM To compare multiparametric normal-resolution(NR)and SR magnetic resonance imaging(MRI...BACKGROUND Deep learning-based super-resolution(SR)reconstruction can obtain high-quality images with more detailed information.AIM To compare multiparametric normal-resolution(NR)and SR magnetic resonance imaging(MRI)in predicting the histopathologic grade in hepatocellular carcinoma.METHODS We retrospectively analyzed a total of 826 patients from two medical centers(training 459;validation 196;test 171).T2-weighted imaging,diffusion-weighted imaging,and portal venous phases were collected.Tumor segmentations were conducted automatically by 3D U-Net.Based on generative adversarial network,we utilized 3D SR reconstruction to produce SR MRI.Radiomics models were developed and validated by XGBoost and Catboost.The predictive efficiency was demonstrated by calibration curves,decision curve analysis,area under the curve(AUC)and net reclassification index(NRI).RESULTS We extracted 3045 radiomic features from both NR and SR MRI,retaining 29 and 28 features,respectively.For XGBoost models,SR MRI yielded higher AUC value than NR MRI in the validation and test cohorts(0.83 vs 0.79;0.80 vs 0.78),respectively.Consistent trends were seen in CatBoost models:SR MRI achieved AUCs of 0.89 and 0.80 compared to NR MRI’s 0.81 and 0.76.NRI indicated that the SR MRI models could improve the prediction accuracy by-1.6%to 20.9%compared to the NR MRI models.CONCLUSION Deep learning-based SR MRI could improve the predictive performance of histopathologic grade in HCC.It may be a powerful tool for better stratification management for patients with operable HCC.展开更多
BACKGROUND Hepatobiliary surgery is complex and requires a thorough understanding of the liver’s anatomy,biliary system,and vasculature.Traditional imaging methods such as computed tomography(CT)and magnetic resonanc...BACKGROUND Hepatobiliary surgery is complex and requires a thorough understanding of the liver’s anatomy,biliary system,and vasculature.Traditional imaging methods such as computed tomography(CT)and magnetic resonance imaging(MRI),although helpful,fail to provide three-dimensional(3D)relationships of these structures,which are critical for planning and executing complicated surgeries.AIM To explore the use of 3D imaging and virtual surgical planning(VSP)technologies to improve surgical accuracy,reduce complications,and enhance patient recovery in hepatobiliary surgeries.METHODS A comprehensive review of studies published between 2017 and 2024 was conducted through PubMed,Scopus,Google Scholar,and Web of Science.Studies selected focused on 3D imaging and VSP applications in hepatobiliary surgery,assessing surgical precision,complications,and patient outcomes.Thirty studies,including randomized controlled trials,cohort studies,and case reports,were included in the final analysis.RESULTS Various 3D imaging modalities,including multidetector CT,MRI,and 3D rotational angiography,provide high-resolution views of the liver’s vascular and biliary anatomy.VSP allows surgeons to simulate complex surgeries,improving preoperative planning and reducing complications like bleeding and bile leaks.Several studies have demonstrated improved surgical precision,reduced complications,and faster recovery times when 3D imaging and VSP were used in complex surgeries.CONCLUSION 3D imaging and VSP technologies significantly enhance the accuracy and outcomes of hepatobiliary surgeries by providing individualized preoperative planning.While promising,further research,particularly randomized controlled trials,is needed to standardize protocols and evaluate long-term efficacy.展开更多
In order to improve the reconstruction accuracy of magnetic resonance imaging(MRI),an accurate natural image compressed sensing(CS)reconstruction network is proposed,which combines the advantages of model-based and de...In order to improve the reconstruction accuracy of magnetic resonance imaging(MRI),an accurate natural image compressed sensing(CS)reconstruction network is proposed,which combines the advantages of model-based and deep learning-based CS-MRI methods.In theory,enhancing geometric texture details in linear reconstruction is possible.First,the optimization problem is decomposed into two problems:linear approximation and geometric compensation.Aimed at the problem of image linear approximation,the data consistency module is used to deal with it.Since the processing process will lose texture details,a neural network layer that explicitly combines image and frequency feature representation is proposed,which is named butterfly dilated geometric distillation network.The network introduces the idea of butterfly operation,skillfully integrates the features of image domain and frequency domain,and avoids the loss of texture details when extracting features in a single domain.Finally,a channel feature fusion module is designed by combining channel attention mechanism and dilated convolution.The attention of the channel makes the final output feature map focus on the more important part,thus improving the feature representation ability.The dilated convolution enlarges the receptive field,thereby obtaining more dense image feature data.The experimental results show that the peak signal-to-noise ratio of the network is 5.43 dB,5.24 dB and 3.89 dB higher than that of ISTA-Net+,FISTA and DGDN networks on the brain data set with a Cartesian sampling mask CS ratio of 10%.展开更多
Stochastic optical reconstruction microscopy(STORM),as a typical technique of single-molecule localization microscopy(SMLM),has overcome the diffraction limit by randomly switching fluorophores between fluorescent and...Stochastic optical reconstruction microscopy(STORM),as a typical technique of single-molecule localization microscopy(SMLM),has overcome the diffraction limit by randomly switching fluorophores between fluorescent and dark states,allowing for the precise localization of isolated emission patterns and the super-resolution reconstruction from millions of localized positions of single fluorophores.A critical factor influencing localization precision is the photo-switching behavior of fluorophores,which is affected by the imaging buffer.The imaging buffer typically comprises oxygen scavengers,photo-switching reagents,and refractive index regulators.Oxygen scavengers help prevent photobleaching,photo-switching reagents assist in facilitating the conversion of fluorophores,and refractive index regulators are used to adjust the refractive index of the solution.The synergistic interaction of these components promotes stable blinking of fluorophores,reduces irreversible photobleaching,and thereby ensures high-quality super-resolution imaging.This review provides a comprehensive overview of the essential compositions and functionalities of imaging buffers used in STORM,serving as a valuable resource for researchers seeking to select appropriate imaging buffers for their experiments.展开更多
Neutron capture event imaging is a novel technique that has the potential to substantially enhance the resolution of existing imaging systems.This study provides a measurement method for neutron capture event distribu...Neutron capture event imaging is a novel technique that has the potential to substantially enhance the resolution of existing imaging systems.This study provides a measurement method for neutron capture event distribution along with multiple reconstruction methods for super-resolution imaging.The proposed technology reduces the point-spread function of an imag-ing system through single-neutron detection and event reconstruction,thereby significantly improving imaging resolution.A single-neutron detection experiment was conducted using a highly practical and efficient^(6)LiF-ZnS scintillation screen of a cold neutron imaging device in the research reactor.In milliseconds of exposure time,a large number of weak light clusters and their distribution in the scintillation screen were recorded frame by frame,to complete single-neutron detection.Several reconstruction algorithms were proposed for the calculations.The location of neutron capture was calculated using several processing methods such as noise removal,filtering,spot segmentation,contour analysis,and local positioning.The proposed algorithm achieved a higher imaging resolution and faster reconstruction speed,and single-neutron super-resolution imaging was realized by combining single-neutron detection experiments and reconstruction calculations.The results show that the resolution of the 100μm thick^(6)LiF-ZnS scintillation screen can be improved from 125 to 40 microns.This indicates that the proposed single-neutron detection and calculation method is effective and can significantly improve imaging resolution.展开更多
Purpose:To assess the clinical efficacy of integrating deep learning reconstruction(DLR)with contrast-enhancement-boost(CE-boost)in 80 kVp head and neck CT angiography(CTA)using substantially lowered radiation and con...Purpose:To assess the clinical efficacy of integrating deep learning reconstruction(DLR)with contrast-enhancement-boost(CE-boost)in 80 kVp head and neck CT angiography(CTA)using substantially lowered radiation and contrast medium(CM)doses,compared to the standard 100 kVp protocol using hybrid iterative reconstruction(HIR).Methods:Sixty-six patients were prospectively enrolled and randomly assigned to one of two groups:the low-dose group(n=33),receiving 80 kVp and 28 mL contrast medium(CM)with a noise index(NI)of 15;and the regular-dose group(n=33),receiving 100 kVp and 40 mL CM with an NI of 10.For the lowdose group,images underwent reconstruction using both hybrid iterative reconstruction(HIR)and deep learning reconstruction(DLR)at mild-,standard-,and strong-strength levels,both before and after combination with contrast enhancement-boost(CE-boost).This generated eight distinct datasets:L-HIR,L-DLR_(mild),L-DLR_(standard),L-DLR_(strong),L-HIR-CE,L-DLR_(mild)-CE,L-DLR_(standard)-CE,and L-DLR_(strong)-CE.Images for the regular-dose group were reconstructed solely with HIR(R-HIR).Quantitative analysis involved calculating and comparing CT attenuation,image noise,signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR)within six key vessels:the aortic arch(AA),internal carotid artery(ICA),external carotid artery(ECA),vertebral arteries(VA),basilar artery(BA),and middle cerebral artery(MCA).Two radiologists independently assessed subjective image quality using a 5-point scale,with statistical significance defined as P<0.05.Results:Compared to the regular-dose group,the low-dose protocol achieved a substantial reduction in contrast media volume(28 mL versus 40 mL,a 30%decrease)and radiation exposure((0.41±0.08)mSv versus(1.18±0.12)mSv,a 65%reduction).Both L-DLR_(standard) and L-DLR_(strong) delivered comparable or superior SNR and CNR across all vascular segments relative to R-HIR.However,subjective image quality scores for L-DLR at all strength levels fell below those for R-HIR(all P<0.05 for both readers).Combining CE-boost with the low-dose protocol significantly enhanced the objective image performance of L-DLR_(strong)-CE(all P<0.05)and produced subjective image scores comparable to R-HIR(reader 1:P=0.15;reader 2:P=0.06).Conclusion:When compared to the standard 100 kVp head and neck CTA,the combination of the DLR and CE-boost techniques at 80 kVp can achieve a 30%reduction in contrast dose and a 65%reduction in radiation dose,while maintaining both objective and subjective image quality.展开更多
A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of...A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.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
A new medical image fusion technique is presented.The method is based on three-dimensional reconstruction.After reconstruction,the three-dimensional volume data is normalized by three-dimensional coordinate conversion...A new medical image fusion technique is presented.The method is based on three-dimensional reconstruction.After reconstruction,the three-dimensional volume data is normalized by three-dimensional coordinate conversion in the same way and intercepted through setting up cutting plane including anatomical structure,as a result two images in entire registration on space and geometry are obtained and the images are fused at last.Compared with traditional two-dimensional fusion technique,three-dimensional fusion technique can not only resolve the different problems existed in the two kinds of images,but also avoid the registration error of the two kinds of images when they have different scan and imaging parameter.The research proves this fusion technique is more exact and has no registration,so it is more adapt to arbitrary medical image fusion with different equipments.展开更多
Three-dimensional(3D)reconstruction of human organs has gained attention in recent years due to advances in the Internet and graphics processing units.In the coming years,most patient care will shift toward this new p...Three-dimensional(3D)reconstruction of human organs has gained attention in recent years due to advances in the Internet and graphics processing units.In the coming years,most patient care will shift toward this new paradigm.However,development of fast and accurate 3D models from medical images or a set of medical scans remains a daunting task due to the number of pre-processing steps involved,most of which are dependent on human expertise.In this review,a survey of pre-processing steps was conducted,and reconstruction techniques for several organs in medical diagnosis were studied.Various methods and principles related to 3D reconstruction were highlighted.The usefulness of 3D reconstruction of organs in medical diagnosis was also highlighted.展开更多
This study proposes an image-based three-dimensional(3D)vector reconstruction of industrial parts that can gener-ate non-uniform rational B-splines(NURBS)surfaces with high fidelity and flexibility.The contributions o...This study proposes an image-based three-dimensional(3D)vector reconstruction of industrial parts that can gener-ate non-uniform rational B-splines(NURBS)surfaces with high fidelity and flexibility.The contributions of this study include three parts:first,a dataset of two-dimensional images is constructed for typical industrial parts,including hex-agonal head bolts,cylindrical gears,shoulder rings,hexagonal nuts,and cylindrical roller bearings;second,a deep learning algorithm is developed for parameter extraction of 3D industrial parts,which can determine the final 3D parameters and pose information of the reconstructed model using two new nets,CAD-ClassNet and CAD-ReconNet;and finally,a 3D vector shape reconstruction of mechanical parts is presented to generate NURBS from the obtained shape parameters.The final reconstructed models show that the proposed approach is highly accurate,efficient,and practical.展开更多
Objective: To evaluate three-dimensional bronchial artery imaging charactersin central lung cancer and applied values with multi-slice spiral CT (MSCT) to provide theoreticalevidence on blood supply and intervention t...Objective: To evaluate three-dimensional bronchial artery imaging charactersin central lung cancer and applied values with multi-slice spiral CT (MSCT) to provide theoreticalevidence on blood supply and intervention therapy. Methods: Eighteen patients with central lungcancer underwent MSCT with real time helical thin-slice CT scanning. Three-dimensional bronchialartery reconstruction was done at the console work-station. The space anatomical characters ofbronchial artery were observed through different rotations. Results: For 6 cases, thethree-dimensional images of bronchial artery (33.33%) could exactly show the origins, the routes(lung inner segment and mediatism segment) and the diameters of bronchial arteries. Vision rate ofbronchial arteries was the highest in pulmonary artery stricture and truncation groups, and thevessels' diameter became larger apparently. These characters demonstrated blood supply of this kindof central lung cancer come from bronchial artery. Volume rendering images were the best ones amongthree-dimensional images. Conclusion: Three-dimensional imaging with MSCT in bronchial artery canreveal the anatomical characters of bronchial artery and provide theoretical evidence on bloodsupply and intervention therapy of central lung cancer.展开更多
基金supported by grants from the National Key Research and Development Plan of China,No.31670986(to QTZ)the Science and Technology Project of Guangdong Province of China,No.2014B020227001,2017A050501017(to QTZ)the Science and Technology Project of Guangzhou of China,No.201807010082(to QTZ),201704030041(to JQ)
文摘The most common methods for three-dimensional reconstruction of peripheral nerve fascicles include histological and radiology techniques. Histological techniques have many drawbacks including an enormous manual workload and poor image registration. Micro-magnetic resonance imaging（Micro-MRI）, an emerging radiology technique, has been used to report results in the brain, liver and tumor tissues. However, micro-MRI usage for obtaining intraneural structures has not been reported. The aim of this study was to present a new imaging method for three-dimensional reconstruction of peripheral nerve fascicles by ~1T micro-MRI. Freshly harvested sciatic nerve samples from an amputated limb were divided into four groups. Two different scanning conditions（Mannerist Solution/GD-DTPA contrast agent, distilled water） were selected, and both T1 and T2 phases programmed for each scanning condition. Three clinical surgeons evaluated the quality of the images via a standardized scale. Moreover, to analyze deformation of the two-dimensional image, the nerve diameter and total area of the micro-MRI images were compared after hematoxylin-eosin staining. The results show that rapid micro-MRI imaging method can be used for three-dimensional reconstruction of the fascicle structure. Nerve sample immersed in contrast agent（Mannerist Solution/GD-DTPA） and scanned in the T1 phase was the best. Moreover, the nerve sample was scanned freshly and can be recycled for other procedures. MRI images show better stability and smaller deformation compared with histological images. In conclusion, micro-MRI provides a feasible and rapid method for three-dimensional reconstruction of peripheral nerve fascicles, which can clearly show the internal structure of the peripheral nerve.
基金supported by the National Natural Science Foundation of China (No. 12220101005)Natural Science Foundation of Jiangsu Province (No. BK20220132)+2 种基金Primary Research and Development Plan of Jiangsu Province (No. BE2019002-3)Fundamental Research Funds for Central Universities (No. NG2022004)the Foundation of the Graduate Innovation Center in NUAA (No. xcxjh20210613)。
文摘A novel and fast three-dimensional reconstruction method for a Compton camera and its performance in radionuclide imaging is proposed and analyzed in this study. The conical surface sampling back-projection method with scattering angle correction(CSS-BP-SC) can quickly perform the back-projection process of the Compton cone and can be used to precompute the list-mode maximum likelihood expectation maximization(LM-MLEM). A dedicated parallel architecture was designed for the graphics processing unit acceleration of the back-projection and iteration stage of the CSS-BP-SC-based LM-MLEM. The imaging results of the two-point source Monte Carlo(MC) simulation demonstrate that by analyzing the full width at half maximum along the three coordinate axes, the CSS-BP-SC-based LM-MLEM can obtain imaging results comparable to those of the traditional reconstruction algorithm, that is, the simple back-projection-based LM-MLEM. The imaging results of the mouse phantom MC simulation and experiment demonstrate that the reconstruction results obtained by the proposed method sufficiently coincide with the set radioactivity distribution, and the speed increased by more than 664 times compared to the traditional reconstruction algorithm in the mouse phantom experiment. The proposed method will further advance the imaging applications of Compton cameras.
基金Project supported by the National Key Research and Development Program of China (Grant No. 2018YFB0504302)Beijing Institute of Technology Research Fund Program for Young Scholars (Grant No. 202122012)。
文摘Existing three-dimensional(3D) imaging technologies have issues such as requiring active illumination, multiple exposures, or coding modulation. We propose a passive single 3D imaging method based on an ordinary imaging system.Using the point spread function of the imaging system to realize the non-coding measurement on the target, the full-focus images and depth information of the 3D target can be extracted from a single two-dimensional(2D) image through the compressed sensing algorithm. Simulation and experiments show that this approach can complete passive 3D imaging based on an ordinary imaging system without any coding operations. This method can achieve millimeter-level vertical resolution under single exposure conditions and has the potential for real-time dynamic 3D imaging. It improves the efficiency of 3D information detection, reduces the complexity of the imaging system, and may be of considerable value to the field of computer vision and other related applications.
基金The National Natural Science Foundation of China(No.60972130)
文摘In order to obtain a better sandstone three-dimensional （3D） reconstruction result which is more similar to the original sample, an algorithm based on stationarity for a two-dimensional （2D） training image is proposed. The second-order statistics based on texture features are analyzed to evaluate the scale stationarity of the training image. The multiple-point statistics of the training image are applied to obtain the multiple-point statistics stationarity estimation by the multi-point density function. The results show that the reconstructed 3D structures are closer to reality when the training image has better scale stationarity and multiple-point statistics stationarity by the indications of local percolation probability and two-point probability. Moreover, training images with higher multiple-point statistics stationarity and lower scale stationarity are likely to obtain closer results to the real 3D structure, and vice versa. Thus, stationarity analysis of the training image has far-reaching significance in choosing a better 2D thin section image for the 3D reconstruction of porous media. Especially, high-order statistics perform better than low-order statistics.
基金Supported by the 2022 Provincial Quality Engineering Project for Higher Education Institutions,No.2022sx031the 2023 Provincial Quality Engineering Project for Higher Education Institutions,No.2023jyxm1071.
文摘BACKGROUND Inguinal hernias are common after surgery.Tension-free repair is widely accepted as the main method for managing inguinal hernias.Adequate exposure,coverage,and repair of the myopectineal orifice(MPO)are necessary.However,due to differences in race and sex,people’s body shapes vary.According to European guidelines,the patch should measure 10 cm×15 cm.If any part of the MPO is dissected,injury to the nerves,vascular network,or organs may occur during surgery,thereby leading to inguinal discomfort,pain,and seroma formation after surgery.Therefore,accurate localization and measurement of the boundary of the MPO are crucial for selecting the optimal patch for inguinal hernia repair.AIM To compare the size of the MPO measured on three-dimensional multislice spiral computed tomography(CT)with that measured via laparoscopy and explore the relevant factors influencing the size of the MPO.METHODS Clinical data from 74 patients who underwent laparoscopic tension-free inguinal hernia repair at the General Surgery Department of the First Affiliated Hospital of Anhui University of Science and Technology between September 2022 and July 2024 were collected and analyzed retrospectively.Transabdominal preperitoneal was performed.Sixty-four males and 10 females,with an average age of 58.30±12.32 years,were included.The clinical data of the patients were collected.The boundary of the MPO was measured on three-dimensional CT images before surgery and then again during transabdominal preperitoneal.All the preoperative and intraoperative data were analyzed via paired t-tests.A t-test was used for comparisons of age,body mass index,and sex between the groups.In the comparative analysis,a P value less than 0.05 indicated a significant difference.RESULTS The boundaries of the MPO on 3-dimensional CT images measured 7.05±0.47 cm and 6.27±0.61 cm,and the area of the MPO was 19.54±3.33 cm^(2).The boundaries of the MPO during surgery were 7.18±0.51 cm and 6.17±0.40 cm.The errors were not statistically significant.However,the intraoperative BD(the width of the MPO,P=0.024,P<0.05)and preoperative AC(the length of the MPO,P=0.045,P<0.05)significantly differed according to sex.The AC and BD measurements before and during surgery were not significantly different according to age,body mass index,hernia side or hernia type(P>0.05).CONCLUSION The application of this technology can aid in determining the most appropriate dissection range and patch size.
基金Supported by the Natural Science Foundation of Fujian Province,No.2022J011442.
文摘BACKGROUND Percutaneous transhepatic biliary drainage(PTBD)is one of the primary clinical treatment options for patients with obstructive jaundice.In recent years,PTBD assisted by three-dimensional(3D)reconstruction technology has been widely implemented,but its advantages over traditional methods remains inconclusive.Thus,a discussion is warranted.AIM To explore the safety and efficacy of 3D reconstruction technology-assisted PTBD.METHODS We systematically searched the databases including the Cochrane Library,PubMed,EMBASE,Web of Science and China National Knowledge Infrastructure.The search period extended from the establishment of each database to November,2024.We screened the literature according to predefined inclusion and exclusion criteria,assessed the quality of the studies,and extracted data.Meta-analysis was performed using Revman 5.4.1 software.RESULTS A total of 15 studies were included,involving 1434 patients.The results of the meta-analysis showed that compared with the traditional group,the overall post-operative complications rate in the 3D reconstruction technology group was significantly lower[odds ratio=0.25;95%confidence interval(CI):0.17-0.36,P<0.00001].The overall puncture success rate in the 3D reconstruction group was better than those in the traditional group(odds ratio=3.61;95%CI:1.98-6.55,P<0.0001).However,there was no significant difference between the two groups in the reduction levels of postoperative total bilirubin(mean difference=-1.38;95%CI:-3.29 to 0.53,P=0.16).Subgroup analysis were conducted on the surgery time according to guidance stages of the 3D reconstruction,3D reconstruction imaging modalities,and types of studies.The results were stable,with no significant changes observed.CONCLUSION 3D reconstruction technology significantly improves the puncture success rate and safety of PTBD.However,it has no significant advantage in bile drainage effectiveness.Continued research is warranted to further explore its clinical value and optimize its application.
文摘Among hyperspectral imaging technologies, interferometric spectral imaging is widely used in remote sening due to advantages of large luminous flux and high resolution. However, with complicated mechanism, interferometric imaging faces the impact of multi-stage degradation. Most exsiting interferometric spectrum reconstruction methods are based on tradition model-based framework with multiple steps, showing poor efficiency and restricted performance. Thus, we propose an interferometric spectrum reconstruction method based on degradation synthesis and deep learning.Firstly, based on imaging mechanism, we proposed an mathematical model of interferometric imaging to analyse the degradation components as noises and trends during imaging. The model consists of three stages, namely instrument degradation, sensing degradation, and signal-independent degradation process. Then, we designed calibration-based method to estimate parameters in the model, of which the results are used for synthesizing realistic dataset for learning-based algorithms.In addition, we proposed a dual-stage interferogram spectrum reconstruction framework, which supports pre-training and integration of denoising DNNs. Experiments exhibits the reliability of our degradation model and synthesized data, and the effectiveness of the proposed reconstruction method.
基金Supported by AI+Health Collaborative Innovation Cultivation Project of Beijing City,No.Z221100003522005.
文摘BACKGROUND Deep learning-based super-resolution(SR)reconstruction can obtain high-quality images with more detailed information.AIM To compare multiparametric normal-resolution(NR)and SR magnetic resonance imaging(MRI)in predicting the histopathologic grade in hepatocellular carcinoma.METHODS We retrospectively analyzed a total of 826 patients from two medical centers(training 459;validation 196;test 171).T2-weighted imaging,diffusion-weighted imaging,and portal venous phases were collected.Tumor segmentations were conducted automatically by 3D U-Net.Based on generative adversarial network,we utilized 3D SR reconstruction to produce SR MRI.Radiomics models were developed and validated by XGBoost and Catboost.The predictive efficiency was demonstrated by calibration curves,decision curve analysis,area under the curve(AUC)and net reclassification index(NRI).RESULTS We extracted 3045 radiomic features from both NR and SR MRI,retaining 29 and 28 features,respectively.For XGBoost models,SR MRI yielded higher AUC value than NR MRI in the validation and test cohorts(0.83 vs 0.79;0.80 vs 0.78),respectively.Consistent trends were seen in CatBoost models:SR MRI achieved AUCs of 0.89 and 0.80 compared to NR MRI’s 0.81 and 0.76.NRI indicated that the SR MRI models could improve the prediction accuracy by-1.6%to 20.9%compared to the NR MRI models.CONCLUSION Deep learning-based SR MRI could improve the predictive performance of histopathologic grade in HCC.It may be a powerful tool for better stratification management for patients with operable HCC.
文摘BACKGROUND Hepatobiliary surgery is complex and requires a thorough understanding of the liver’s anatomy,biliary system,and vasculature.Traditional imaging methods such as computed tomography(CT)and magnetic resonance imaging(MRI),although helpful,fail to provide three-dimensional(3D)relationships of these structures,which are critical for planning and executing complicated surgeries.AIM To explore the use of 3D imaging and virtual surgical planning(VSP)technologies to improve surgical accuracy,reduce complications,and enhance patient recovery in hepatobiliary surgeries.METHODS A comprehensive review of studies published between 2017 and 2024 was conducted through PubMed,Scopus,Google Scholar,and Web of Science.Studies selected focused on 3D imaging and VSP applications in hepatobiliary surgery,assessing surgical precision,complications,and patient outcomes.Thirty studies,including randomized controlled trials,cohort studies,and case reports,were included in the final analysis.RESULTS Various 3D imaging modalities,including multidetector CT,MRI,and 3D rotational angiography,provide high-resolution views of the liver’s vascular and biliary anatomy.VSP allows surgeons to simulate complex surgeries,improving preoperative planning and reducing complications like bleeding and bile leaks.Several studies have demonstrated improved surgical precision,reduced complications,and faster recovery times when 3D imaging and VSP were used in complex surgeries.CONCLUSION 3D imaging and VSP technologies significantly enhance the accuracy and outcomes of hepatobiliary surgeries by providing individualized preoperative planning.While promising,further research,particularly randomized controlled trials,is needed to standardize protocols and evaluate long-term efficacy.
基金the National Natural Science Foundation of China(No.61962032)。
文摘In order to improve the reconstruction accuracy of magnetic resonance imaging(MRI),an accurate natural image compressed sensing(CS)reconstruction network is proposed,which combines the advantages of model-based and deep learning-based CS-MRI methods.In theory,enhancing geometric texture details in linear reconstruction is possible.First,the optimization problem is decomposed into two problems:linear approximation and geometric compensation.Aimed at the problem of image linear approximation,the data consistency module is used to deal with it.Since the processing process will lose texture details,a neural network layer that explicitly combines image and frequency feature representation is proposed,which is named butterfly dilated geometric distillation network.The network introduces the idea of butterfly operation,skillfully integrates the features of image domain and frequency domain,and avoids the loss of texture details when extracting features in a single domain.Finally,a channel feature fusion module is designed by combining channel attention mechanism and dilated convolution.The attention of the channel makes the final output feature map focus on the more important part,thus improving the feature representation ability.The dilated convolution enlarges the receptive field,thereby obtaining more dense image feature data.The experimental results show that the peak signal-to-noise ratio of the network is 5.43 dB,5.24 dB and 3.89 dB higher than that of ISTA-Net+,FISTA and DGDN networks on the brain data set with a Cartesian sampling mask CS ratio of 10%.
基金funded by the National Natural Science Foundation of China(No.62305041)the Natural Science Foundation of Liaoning Province(No.2023-MS-103)。
文摘Stochastic optical reconstruction microscopy(STORM),as a typical technique of single-molecule localization microscopy(SMLM),has overcome the diffraction limit by randomly switching fluorophores between fluorescent and dark states,allowing for the precise localization of isolated emission patterns and the super-resolution reconstruction from millions of localized positions of single fluorophores.A critical factor influencing localization precision is the photo-switching behavior of fluorophores,which is affected by the imaging buffer.The imaging buffer typically comprises oxygen scavengers,photo-switching reagents,and refractive index regulators.Oxygen scavengers help prevent photobleaching,photo-switching reagents assist in facilitating the conversion of fluorophores,and refractive index regulators are used to adjust the refractive index of the solution.The synergistic interaction of these components promotes stable blinking of fluorophores,reduces irreversible photobleaching,and thereby ensures high-quality super-resolution imaging.This review provides a comprehensive overview of the essential compositions and functionalities of imaging buffers used in STORM,serving as a valuable resource for researchers seeking to select appropriate imaging buffers for their experiments.
基金supported by the National Natural Science Foundation of China(Nos.12205271,12075217,U20B2011,and 51978218)Sichuan Science and Technology Program(No.2019ZDZX0010)the National Key R&D Program of China(No.2022YFA1604002).
文摘Neutron capture event imaging is a novel technique that has the potential to substantially enhance the resolution of existing imaging systems.This study provides a measurement method for neutron capture event distribution along with multiple reconstruction methods for super-resolution imaging.The proposed technology reduces the point-spread function of an imag-ing system through single-neutron detection and event reconstruction,thereby significantly improving imaging resolution.A single-neutron detection experiment was conducted using a highly practical and efficient^(6)LiF-ZnS scintillation screen of a cold neutron imaging device in the research reactor.In milliseconds of exposure time,a large number of weak light clusters and their distribution in the scintillation screen were recorded frame by frame,to complete single-neutron detection.Several reconstruction algorithms were proposed for the calculations.The location of neutron capture was calculated using several processing methods such as noise removal,filtering,spot segmentation,contour analysis,and local positioning.The proposed algorithm achieved a higher imaging resolution and faster reconstruction speed,and single-neutron super-resolution imaging was realized by combining single-neutron detection experiments and reconstruction calculations.The results show that the resolution of the 100μm thick^(6)LiF-ZnS scintillation screen can be improved from 125 to 40 microns.This indicates that the proposed single-neutron detection and calculation method is effective and can significantly improve imaging resolution.
基金National Natural Science Foundation of China(82001814)National High Level Hospital Clinical Research Funding(grant number 2022-PUMCH-B-067)+1 种基金National High Level Hospital Clinical Research Funding(grant number 2022-PUMCH-B-068)2021 SKY Imaging Research Fund of the Chinese Internatinal Medical Foundation(Z-2014-07-2101).
文摘Purpose:To assess the clinical efficacy of integrating deep learning reconstruction(DLR)with contrast-enhancement-boost(CE-boost)in 80 kVp head and neck CT angiography(CTA)using substantially lowered radiation and contrast medium(CM)doses,compared to the standard 100 kVp protocol using hybrid iterative reconstruction(HIR).Methods:Sixty-six patients were prospectively enrolled and randomly assigned to one of two groups:the low-dose group(n=33),receiving 80 kVp and 28 mL contrast medium(CM)with a noise index(NI)of 15;and the regular-dose group(n=33),receiving 100 kVp and 40 mL CM with an NI of 10.For the lowdose group,images underwent reconstruction using both hybrid iterative reconstruction(HIR)and deep learning reconstruction(DLR)at mild-,standard-,and strong-strength levels,both before and after combination with contrast enhancement-boost(CE-boost).This generated eight distinct datasets:L-HIR,L-DLR_(mild),L-DLR_(standard),L-DLR_(strong),L-HIR-CE,L-DLR_(mild)-CE,L-DLR_(standard)-CE,and L-DLR_(strong)-CE.Images for the regular-dose group were reconstructed solely with HIR(R-HIR).Quantitative analysis involved calculating and comparing CT attenuation,image noise,signal-to-noise ratio(SNR),and contrast-to-noise ratio(CNR)within six key vessels:the aortic arch(AA),internal carotid artery(ICA),external carotid artery(ECA),vertebral arteries(VA),basilar artery(BA),and middle cerebral artery(MCA).Two radiologists independently assessed subjective image quality using a 5-point scale,with statistical significance defined as P<0.05.Results:Compared to the regular-dose group,the low-dose protocol achieved a substantial reduction in contrast media volume(28 mL versus 40 mL,a 30%decrease)and radiation exposure((0.41±0.08)mSv versus(1.18±0.12)mSv,a 65%reduction).Both L-DLR_(standard) and L-DLR_(strong) delivered comparable or superior SNR and CNR across all vascular segments relative to R-HIR.However,subjective image quality scores for L-DLR at all strength levels fell below those for R-HIR(all P<0.05 for both readers).Combining CE-boost with the low-dose protocol significantly enhanced the objective image performance of L-DLR_(strong)-CE(all P<0.05)and produced subjective image scores comparable to R-HIR(reader 1:P=0.15;reader 2:P=0.06).Conclusion:When compared to the standard 100 kVp head and neck CTA,the combination of the DLR and CE-boost techniques at 80 kVp can achieve a 30%reduction in contrast dose and a 65%reduction in radiation dose,while maintaining both objective and subjective image quality.
文摘A method and procedure is presented to reconstruct three-dimensional(3D) positions of scattering centers from multiple synthetic aperture radar(SAR) images. Firstly, two-dimensional(2D) attribute scattering centers of targets are extracted from 2D SAR images. Secondly, similarity measure is developed based on 2D attributed scatter centers' location, type, and radargrammetry principle between multiple SAR images. By this similarity, we can associate 2D scatter centers and then obtain candidate 3D scattering centers. Thirdly, these candidate scattering centers are clustered in 3D space to reconstruct final 3D positions. Compared with presented methods, the proposed method has a capability of describing distributed scattering center, reduces false and missing 3D scattering centers, and has fewer restrictionson modeling data. Finally, results of experiments have demonstrated the effectiveness of the proposed method.
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.
文摘A new medical image fusion technique is presented.The method is based on three-dimensional reconstruction.After reconstruction,the three-dimensional volume data is normalized by three-dimensional coordinate conversion in the same way and intercepted through setting up cutting plane including anatomical structure,as a result two images in entire registration on space and geometry are obtained and the images are fused at last.Compared with traditional two-dimensional fusion technique,three-dimensional fusion technique can not only resolve the different problems existed in the two kinds of images,but also avoid the registration error of the two kinds of images when they have different scan and imaging parameter.The research proves this fusion technique is more exact and has no registration,so it is more adapt to arbitrary medical image fusion with different equipments.
文摘Three-dimensional(3D)reconstruction of human organs has gained attention in recent years due to advances in the Internet and graphics processing units.In the coming years,most patient care will shift toward this new paradigm.However,development of fast and accurate 3D models from medical images or a set of medical scans remains a daunting task due to the number of pre-processing steps involved,most of which are dependent on human expertise.In this review,a survey of pre-processing steps was conducted,and reconstruction techniques for several organs in medical diagnosis were studied.Various methods and principles related to 3D reconstruction were highlighted.The usefulness of 3D reconstruction of organs in medical diagnosis was also highlighted.
基金supported by the Aeronautical Science Foundation of China,No.2023Z0680510022021 Special Scientific Research on Civil Aircraft Project+1 种基金the Natural Science Foundation of China,Nos.61572056 and 61872347the Special Plan for the Development of Distinguished Young Scientists of ISCAS,No.Y8RC535018.
文摘This study proposes an image-based three-dimensional(3D)vector reconstruction of industrial parts that can gener-ate non-uniform rational B-splines(NURBS)surfaces with high fidelity and flexibility.The contributions of this study include three parts:first,a dataset of two-dimensional images is constructed for typical industrial parts,including hex-agonal head bolts,cylindrical gears,shoulder rings,hexagonal nuts,and cylindrical roller bearings;second,a deep learning algorithm is developed for parameter extraction of 3D industrial parts,which can determine the final 3D parameters and pose information of the reconstructed model using two new nets,CAD-ClassNet and CAD-ReconNet;and finally,a 3D vector shape reconstruction of mechanical parts is presented to generate NURBS from the obtained shape parameters.The final reconstructed models show that the proposed approach is highly accurate,efficient,and practical.
文摘Objective: To evaluate three-dimensional bronchial artery imaging charactersin central lung cancer and applied values with multi-slice spiral CT (MSCT) to provide theoreticalevidence on blood supply and intervention therapy. Methods: Eighteen patients with central lungcancer underwent MSCT with real time helical thin-slice CT scanning. Three-dimensional bronchialartery reconstruction was done at the console work-station. The space anatomical characters ofbronchial artery were observed through different rotations. Results: For 6 cases, thethree-dimensional images of bronchial artery (33.33%) could exactly show the origins, the routes(lung inner segment and mediatism segment) and the diameters of bronchial arteries. Vision rate ofbronchial arteries was the highest in pulmonary artery stricture and truncation groups, and thevessels' diameter became larger apparently. These characters demonstrated blood supply of this kindof central lung cancer come from bronchial artery. Volume rendering images were the best ones amongthree-dimensional images. Conclusion: Three-dimensional imaging with MSCT in bronchial artery canreveal the anatomical characters of bronchial artery and provide theoretical evidence on bloodsupply and intervention therapy of central lung cancer.
