The translation of ancient Chinese cultural artifacts terminology in museums plays a pivotal role in facilitating cross-cultural communication and preserving cultural heritage in the context of globalization.Through f...The translation of ancient Chinese cultural artifacts terminology in museums plays a pivotal role in facilitating cross-cultural communication and preserving cultural heritage in the context of globalization.Through field research in over ten Chinese museums and analysis of more than 800 terms,this paper explores the most effective translation methods for such terminology,focusing on transliteration and literal translation under the strategy of foreignization as well as liberal translation and imitation under the domesticating strategy.Standardized terminology not only prevents ambiguities but also bridges cultural gaps by preserving phonetic authenticity while contextualizing functionality.By refining translation practices,museums can better fulfill their mission as bridges between cultures,promoting global appreciation of China’s rich historical and artistic legacy.展开更多
This study aims to clarify the conceptual characteristics of artifact utilization in nursing practice instruction. Five selected articles were analyzed using the concept analysis method by Walker and Avant. The attrib...This study aims to clarify the conceptual characteristics of artifact utilization in nursing practice instruction. Five selected articles were analyzed using the concept analysis method by Walker and Avant. The attributes, antecedents, and consequences of the concept were extracted from the target literature. The analysis revealed two attributes (“connecting people to people” and “connecting people to objects”);two antecedents (“recognition of artifacts” and “selection of artifacts”);and two consequences (“designing a fulfilling learning environment” and “improving the quality of education”). The concept was defined as “promoting the utilization of artifacts by recognizing and selecting them, connecting people to people and people to objects, designing a fulfilling learning environment, and improving the quality of education”.展开更多
BACKGROUND Posterior lumbar interbody fusion has good clinical results,but adjacent segment disease(ASD)affects its long-term efficacy.In patients with L4-5 fusion who were followed up for more than 10 years,the ASD i...BACKGROUND Posterior lumbar interbody fusion has good clinical results,but adjacent segment disease(ASD)affects its long-term efficacy.In patients with L4-5 fusion who were followed up for more than 10 years,the ASD incidence was 33.3%.Magnetic resonance imaging(MRI)is key for ASD diagnosis,but metal artifacts from internal fixation limit its use;therefore,removing the artifacts is crucial for ASD diagnosis and treatment.AIM To evaluate the value of WARP MRI for patients with lumbar ASD.METHODS In our hospital,the lumbar spines of patients with ASD were assessed via lumbar MRI,including conventional sequences and sequences for artifacts.A PACS workstation was used for image measurement,analysis,and assessment,which mainly included measurement of the internal fixation implant artifact area,evaluation of the visibility of the anatomical structures surrounding the implant,and diagnostic assessment of ASD in the section.Conventional MRI data sequences and artifacts to sequence the contrast analysis of the MRI data.RESULTS A total of 30 patients with ASD after lumbar fusion and internal fixation were included in the study;the patients included 13 male and 17 female patients and were aged 66.03±5.83 years.The metal artifact area of the WARP T2-tirm sequence was significantly smaller than that of the conventional STIR sequence[(20.85±6.27)cm²vs(50.56±8.55)cm²,P<0.01].The WARP T2-tirm sequence was observed around the implants,pedicles,intervertebral foramen,and vertebral bodies,and the conventional STIR sequence clearly displayed nerve roots within the intervertebral foramen.In all 30 patients,all adjacent segments of the WARP T2-tirm sequence could be clearly observed(above Grade 4),whereas it was difficult to observe these segments in the conventional STIR sequence due to the presence of more severe metal artifacts.CONCLUSION WARP sequences can significantly reduce the artifact area in the sagittal and cross-sectional images of titanium alloy spinal fixation,providing a good imaging reference for the diagnosis of ASD.展开更多
Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts ...Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images.We proposed a deep learning-based inpainting method of saturation artifacts in this paper.The generation mechanism of saturation artifacts was analyzed,and experimental and simulated datasets were built based on the mechanism.Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs.The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility,strong generalization,and robustness.展开更多
This study addresses challenges in fetal magnetic resonance imaging (MRI) related to motion artifacts, maternal respiration, and hardware limitations. To enhance MRI quality, we employ deep learning techniques, specif...This study addresses challenges in fetal magnetic resonance imaging (MRI) related to motion artifacts, maternal respiration, and hardware limitations. To enhance MRI quality, we employ deep learning techniques, specifically utilizing Cycle GAN. Synthetic pairs of images, simulating artifacts in fetal MRI, are generated to train the model. Our primary contribution is the use of Cycle GAN for fetal MRI restoration, augmented by artificially corrupted data. We compare three approaches (supervised Cycle GAN, Pix2Pix, and Mobile Unet) for artifact removal. Experimental results demonstrate that the proposed supervised Cycle GAN effectively removes artifacts while preserving image details, as validated through Structural Similarity Index Measure (SSIM) and normalized Mean Absolute Error (MAE). The method proves comparable to alternatives but avoids the generation of spurious regions, which is crucial for medical accuracy.展开更多
Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the comp...Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.展开更多
The importance of the accuracy of preparing biological specimen as histological sections that can be examined under a microscope lies in reflecting a true image of the tissue that includes all its components, which ar...The importance of the accuracy of preparing biological specimen as histological sections that can be examined under a microscope lies in reflecting a true image of the tissue that includes all its components, which are used in scientific research or for the purpose of diagnosing various diseases of the body. Despite this, some cellular structures within the tissue may suffer from some alterations that result from the appearance of defects during any stage of preparing these microscopic sections, which alter or interfere with the precise cellular structures and morphology that constitute the tissue and thus give a different image for tissue features and cause confusion in the work histopathologist in the diagnosis. There are several reasons that can cause a misdiagnosis of the sample that occurs during the surgical separation process or after separation during the stages of microscopic preparation techniques from fixation stage, tissue processing, embedding or microtomy, staining until mounting procedures. The constant need to identify these defects and their causes in addition to try to reduce them is one of the biggest challenges evident in pathology laboratories. Therefore, this study aims to review the most common defects that occur in any stage of tissue processing, with an explanation of their causes and appropriate ways to avoid them.展开更多
This study presents an energy consumption(EC)forecasting method for laser melting manufacturing of metal artifacts based on fusionable transfer learning(FTL).To predict the EC of manufacturing products,particularly fr...This study presents an energy consumption(EC)forecasting method for laser melting manufacturing of metal artifacts based on fusionable transfer learning(FTL).To predict the EC of manufacturing products,particularly from scale-down to scale-up,a general paradigm was first developed by categorizing the overall process into three main sub-steps.The operating electrical power was further formulated as a combinatorial function,based on which an operator learning network was adopted to fit the nonlinear relations between the fabricating arguments and EC.Parallel-arranged networks were constructed to investigate the impacts of fabrication variables and devices on power.Considering the interconnections among these factors,the outputs of the neural networks were blended and fused to jointly predict the electrical power.Most innovatively,large artifacts can be decomposed into timedependent laser-scanning trajectories,which can be further transformed into fusionable information via neural networks,inspired by large language model.Accordingly,transfer learning can deal with either scale-down or scale-up forecasting,namely,FTL with scalability within artifact structures.The effectiveness of the proposed FTL was verified through physical fabrication experiments via laser powder bed fusion.The relative error of the average and overall EC predictions based on FTL was maintained below 0.83%.The melting fusion quality was examined using metallographic diagrams.The proposed FTL framework can forecast the EC of scaled structures,which is particularly helpful in price estimation and quotation of large metal products towards carbon peaking and carbon neutrality.展开更多
This paper proposes a new adaptive post-filtering algorithm to remove coding artifacts in block-based video coder. The proposed method concentrates on blocking and ringing artifacts removal. For de-blocking, the block...This paper proposes a new adaptive post-filtering algorithm to remove coding artifacts in block-based video coder. The proposed method concentrates on blocking and ringing artifacts removal. For de-blocking, the blocking strength is identified to determine the filtering range, and the maximum quantization parameter of the image is used to adapt the 1D fuzzy filter. For de-ringing, besides the edge detection, a complementary ringing detection method is proposed to locate the neglected ringing blocks, and the gradient threshold is adopted to adjust the parameter of 2D fuzzy filter. Experiments are performed on the MPEG-4 sequences. Compared with other methods, the proposed one achieves better detail preservation and artifacts removal performance with lower computational cost.展开更多
Removing different types of artifacts from the electroencephalography(EEG)recordings is a critical step in performing EEG signal analysis and diagnosis.Most of the existing algorithms aim for removing single type of a...Removing different types of artifacts from the electroencephalography(EEG)recordings is a critical step in performing EEG signal analysis and diagnosis.Most of the existing algorithms aim for removing single type of artifacts,leading to a complex system if an EEG recording contains different types of artifacts.With the advancement in wearable technologies,it is necessary to develop an energy-efficient algorithm to deal with different types of artifacts for single-channel wearable EEG devices.In this paper,an automatic EEG artifact removal algorithm is proposed that effectively reduces three types of artifacts,i.e.,ocular artifact(OA),transmission-line/harmonic-wave artifact(TA/HA),and muscle artifact(MA),from a single-channel EEG recording.The effectiveness of the proposed algorithm is verified on both simulated noisy EEG signals and real EEG from CHB-MIT dataset.The experimental results show that the proposed algorithm effectively suppresses OA,MA and TA/HA from a single-channel EEG recording as well as physical movement artifact.展开更多
A simulation method is proposed to predict the motion artifacts of plasma display panels （PDPs）. The method simulates the behavior of the human vision system when perceiving moving objects. The simulation is based o...A simulation method is proposed to predict the motion artifacts of plasma display panels （PDPs）. The method simulates the behavior of the human vision system when perceiving moving objects. The simulation is based on the measured temporal light properties of the display for each gray level and each phosphor. Both the effect of subfield arrangement and phosphor decay are involved. A novel algorithm is proposed to improve the calculation speed. The simulation model manages to predict the appearance of the motion image perceived by a human with a still image. The results are validated by a set of perceptual evaluation experiments. This rapid and accurate prediction of motion artifacts enables objective characterization of the PDP performance in this aspect.展开更多
X-ray-induced acoustic computed tomography(XACT)is a hybrid imaging modality for detecting X-ray absorption distribution via ultrasound emission.It facilitates imaging from a single projection X-ray illumination,thus ...X-ray-induced acoustic computed tomography(XACT)is a hybrid imaging modality for detecting X-ray absorption distribution via ultrasound emission.It facilitates imaging from a single projection X-ray illumination,thus reducing the radiation exposure and improving imaging speed.Nonuniform detector response caused by the interference between multichannel data acquisition for ring array transducers and amplifier systems yields ring artifacts in the reconstructed XACT images,which compromises the image quality.We propose model-based algorithms for ring artifacts corrected XACT imaging and demonstrate their effcacy on numerical and experimental measurements.The corrected reconstructions indicate significantly reduced ring artifacts as compared to their conventional counterparts.展开更多
This review paper aims to summarize cardiac CT blooming artifacts,how they present clinically and what their root causes and potential solutions are.A literature survey was performed covering any publications with a s...This review paper aims to summarize cardiac CT blooming artifacts,how they present clinically and what their root causes and potential solutions are.A literature survey was performed covering any publications with a specific interest in calcium blooming and stent blooming in cardiac CT.The claims from literature are compared and interpreted,aiming at narrowing down the root causes and most promising solutions for blooming artifacts.More than 30 journal publications were identified with specific relevance to blooming artifacts.The main reported causes of blooming artifacts are the partial volume effect,motion artifacts and beam hardening.The proposed solutions are classified as high-resolution CT hardware,high-resolution CT reconstruction,subtraction techniques and post-processing techniques,with a special emphasis on deep learning(DL)techniques.The partial volume effect is the leading cause of blooming artifacts.The partial volume effect can be minimized by increasing the CT spatial resolution through higherresolution CT hardware or advanced high-resolution CT reconstruction.In addition,DL techniques have shown great promise to correct for blooming artifacts.A combination of these techniques could avoid repeat scans for subtraction techniques.展开更多
BACKGROUND Endoscopy artifacts are widespread in real capsule endoscopy(CE)images but not in high-quality standard datasets.AIM To improve the segmentation performance of polyps from CE images with artifacts based on ...BACKGROUND Endoscopy artifacts are widespread in real capsule endoscopy(CE)images but not in high-quality standard datasets.AIM To improve the segmentation performance of polyps from CE images with artifacts based on ensemble learning.METHODS We collected 277 polyp images with CE artifacts from 5760 h of videos from 480 patients at Guangzhou First People’s Hospital from January 2016 to December 2019.Two public high-quality standard external datasets were retrieved and used for the comparison experiments.For each dataset,we randomly segmented the data into training,validation,and testing sets for model training,selection,and testing.We compared the performance of the base models and the ensemble model in segmenting polyps from images with artifacts.RESULTS The performance of the semantic segmentation model was affected by artifacts in the sample images,which also affected the results of polyp detection by CE using a single model.The evaluation based on real datasets with artifacts and standard datasets showed that the ensemble model of all state-of-the-art models performed better than the best corresponding base learner on the real dataset with artifacts.Compared with the corresponding optimal base learners,the intersection over union(IoU)and dice of the ensemble learning model increased to different degrees,ranging from 0.08%to 7.01%and 0.61%to 4.93%,respectively.Moreover,in the standard datasets without artifacts,most of the ensemble models were slightly better than the base learner,as demonstrated by the IoU and dice increases ranging from-0.28%to 1.20%and-0.61%to 0.76%,respectively.CONCLUSION Ensemble learning can improve the segmentation accuracy of polyps from CE images with artifacts.Our results demonstrated an improvement in the detection rate of polyps with interference from artifacts.展开更多
Interferometric synthetic aperture radar(InSAR)has been widely used to measure ground displacements related to geophysical and anthropic activities over the past three decades.Satellite SAR systems use microwave signa...Interferometric synthetic aperture radar(InSAR)has been widely used to measure ground displacements related to geophysical and anthropic activities over the past three decades.Satellite SAR systems use microwave signals that interact with the ionosphere when they travel through it during the imaging processes.In this context,ionospheric variations can significantly contaminate SAR imagery,which in turn affects spaceborne InSAR measurements.This bias also leads to a decrease in the coherence and accuracy of InSAR measurements,especially for the low-frequency SAR systems.In this paper,we give an overview of the latest methods for mitigating the ionospheric contributions in InSAR,including Faraday rotation method,azimuth shift method,and range split-spectrum method,and only focus on the single pair of InSAR interferograms.The current challenges and future perspectives are outlined at the end of this paper.展开更多
Microwave-induced thermoacoustic imaging(MI-TAI)remains one of the focus of attention among biomedical imaging modalities over the last decade.However,the transmission and dis-tribution of microwave inside bio-tissues...Microwave-induced thermoacoustic imaging(MI-TAI)remains one of the focus of attention among biomedical imaging modalities over the last decade.However,the transmission and dis-tribution of microwave inside bio-tissues are complicated,thus result in severe artifacts.In this study,to reveal the underlying mechanisms of artifacts,we deeply investigate the distribution of specific absorption rate(SAR)inside tissue-mimicking phantoms with varied morphological features using both mathematical simulations and corresponding experiments.Our simulated results,which are confirmed by the associated experimental results,show that the SAR distri-bution highly depends on the geometries of the imaging targets and the polarizing features of the microwave.In addition,we propose the potential mechanisms including Mie-scattering,Fabry-Perot-feature,small curvature effect to interpret the diffraction effect in different scenarios,which may provide basic guidance to predict and distinguish the artifacts for TAI in both fundamental and clinical studies.展开更多
X-ray dark-field imaging using a grating interferometer has shown potential benefits for a variety of applications in recent years.X-ray dark-field image is commonly retrieved by using discrete Fourier transform from ...X-ray dark-field imaging using a grating interferometer has shown potential benefits for a variety of applications in recent years.X-ray dark-field image is commonly retrieved by using discrete Fourier transform from the acquired phasestepping data.The retrieval process assumes a constant phase step size and a constant flux for each stepped grating position.However,stepping errors and flux fluctuations inevitably occur due to external vibrations and/or thermal drift during data acquisition.Previous studies have shown that those influences introduce errors in the acquired phase-stepping data,which cause obvious moiréartifacts in the retrieved refraction image.This work investigates moiréartifacts in x-ray dark-field imaging as a result of flux fluctuations.For the retrieved mean intensity,amplitude,visibility and dark-field images,the dependence of moiréartifacts on flux fluctuation factors is theoretically derived respectively by using a first-order Taylor series expansion.Results of synchrotron radiation experiments verify the validity of the derived analytical formulas.The spatial frequency characteristics of moiréartifacts are analyzed and compared to those induced by phase-stepping errors.It illustrates that moiréartifacts can be estimated by a weighted mean of flux fluctuation factors,with the weighting factors dependent on the moiréphase and different greatly for each retrieved image.Furthermore,moiréartifacts can even be affected by object’s features not displayed in the particular contrast.These results can be used to interpret images correctly,identify sources of moiréartifacts,and develop dedicated algorithms to remove moiréartifacts in the retrieved multi-contrast images.展开更多
This study presents a robustness optimization method for rapid prototyping(RP)of functional artifacts based on visualized computing digital twins(VCDT).A generalized multiobjective robustness optimization model for RP...This study presents a robustness optimization method for rapid prototyping(RP)of functional artifacts based on visualized computing digital twins(VCDT).A generalized multiobjective robustness optimization model for RP of scheme design prototype was first built,where thermal,structural,and multidisciplinary knowledge could be integrated for visualization.To implement visualized computing,the membership function of fuzzy decision-making was optimized using a genetic algorithm.Transient thermodynamic,structural statics,and flow field analyses were conducted,especially for glass fiber composite materials,which have the characteristics of high strength,corrosion resistance,temperature resistance,dimensional stability,and electrical insulation.An electrothermal experiment was performed by measuring the temperature and changes in temperature during RP.Infrared thermographs were obtained using thermal field measurements to determine the temperature distribution.A numerical analysis of a lightweight ribbed ergonomic artifact is presented to illustrate the VCDT.Moreover,manufacturability was verified based on a thermal-solid coupled finite element analysis.The physical experiment and practice proved that the proposed VCDT provided a robust design paradigm for a layered RP between the steady balance of electrothermal regulation and manufacturing efficacy under hybrid uncertainties.展开更多
JPEG-Compatibility steganalysis detects the presence of secret message embedded in the JPEG decompressed images and estimates the embedding rate. We propose a JPEG-Compatibility steganalysis algorithm that estimates t...JPEG-Compatibility steganalysis detects the presence of secret message embedded in the JPEG decompressed images and estimates the embedding rate. We propose a JPEG-Compatibility steganalysis algorithm that estimates the embedding rate based on the difference between the stego image and its recompression based predicted co-vet image. In particular, compression artifacts and embedding changes are distinguished based on the amplitude of pixel value changes. This is done independent of the embedding positions, thus is effective for both content non-adaptive and content adaptive steganography. In addition, we also improve the recompression prediction scheme to more accurately estimate the JPEG quantization table. Experimental results show that the proposed algorithm is significantly more effective in detecting spatial ±1 steganography across a wide range of quality factors and embedding rates, when compared to the previous works.展开更多
Ring artifacts will happen mostly when the detector has inconsistent response among the detector channels,and the characteristic produced rings centered in the iso-center in the reconstructed slices inevitably affect ...Ring artifacts will happen mostly when the detector has inconsistent response among the detector channels,and the characteristic produced rings centered in the iso-center in the reconstructed slices inevitably affect the recognition and analysis of the corresponding sample structures in neutron computed tomography(CT).In this work,a ring correction method based on the projection-field(RCP)is proposed,it is a pre-processing method and provides the corrected projection data directly,which is also conducive to efficient data storage and other algorithmic researches.Simulation and physical experiments are performed for verifying the effect of the method,and one of the correction methods based on the image-field is used for comparison.The results demonstrate that the RCP can correct the ring artifacts well without reducing the image resolution or over-correction.展开更多
文摘The translation of ancient Chinese cultural artifacts terminology in museums plays a pivotal role in facilitating cross-cultural communication and preserving cultural heritage in the context of globalization.Through field research in over ten Chinese museums and analysis of more than 800 terms,this paper explores the most effective translation methods for such terminology,focusing on transliteration and literal translation under the strategy of foreignization as well as liberal translation and imitation under the domesticating strategy.Standardized terminology not only prevents ambiguities but also bridges cultural gaps by preserving phonetic authenticity while contextualizing functionality.By refining translation practices,museums can better fulfill their mission as bridges between cultures,promoting global appreciation of China’s rich historical and artistic legacy.
文摘This study aims to clarify the conceptual characteristics of artifact utilization in nursing practice instruction. Five selected articles were analyzed using the concept analysis method by Walker and Avant. The attributes, antecedents, and consequences of the concept were extracted from the target literature. The analysis revealed two attributes (“connecting people to people” and “connecting people to objects”);two antecedents (“recognition of artifacts” and “selection of artifacts”);and two consequences (“designing a fulfilling learning environment” and “improving the quality of education”). The concept was defined as “promoting the utilization of artifacts by recognizing and selecting them, connecting people to people and people to objects, designing a fulfilling learning environment, and improving the quality of education”.
基金Supported by Shanghai Tongren Hospital Scientific Research Funds,No.TRKYRC-xx202203Shanghai Municipal Health Commission,No.2022YQ006Science and Technology Commission of Shanghai Municipality,No.22ZR1457200.
文摘BACKGROUND Posterior lumbar interbody fusion has good clinical results,but adjacent segment disease(ASD)affects its long-term efficacy.In patients with L4-5 fusion who were followed up for more than 10 years,the ASD incidence was 33.3%.Magnetic resonance imaging(MRI)is key for ASD diagnosis,but metal artifacts from internal fixation limit its use;therefore,removing the artifacts is crucial for ASD diagnosis and treatment.AIM To evaluate the value of WARP MRI for patients with lumbar ASD.METHODS In our hospital,the lumbar spines of patients with ASD were assessed via lumbar MRI,including conventional sequences and sequences for artifacts.A PACS workstation was used for image measurement,analysis,and assessment,which mainly included measurement of the internal fixation implant artifact area,evaluation of the visibility of the anatomical structures surrounding the implant,and diagnostic assessment of ASD in the section.Conventional MRI data sequences and artifacts to sequence the contrast analysis of the MRI data.RESULTS A total of 30 patients with ASD after lumbar fusion and internal fixation were included in the study;the patients included 13 male and 17 female patients and were aged 66.03±5.83 years.The metal artifact area of the WARP T2-tirm sequence was significantly smaller than that of the conventional STIR sequence[(20.85±6.27)cm²vs(50.56±8.55)cm²,P<0.01].The WARP T2-tirm sequence was observed around the implants,pedicles,intervertebral foramen,and vertebral bodies,and the conventional STIR sequence clearly displayed nerve roots within the intervertebral foramen.In all 30 patients,all adjacent segments of the WARP T2-tirm sequence could be clearly observed(above Grade 4),whereas it was difficult to observe these segments in the conventional STIR sequence due to the presence of more severe metal artifacts.CONCLUSION WARP sequences can significantly reduce the artifact area in the sagittal and cross-sectional images of titanium alloy spinal fixation,providing a good imaging reference for the diagnosis of ASD.
基金supported by the National Natural Science Foundation of China(62375144 and 61875092)Tianjin Foundation of Natural Science(21JCYBJC00260)Beijing-Tianjin-Hebei Basic Research Cooperation Special Program(19JCZDJC65300).
文摘Limited by the dynamic range of the detector,saturation artifacts usually occur in optical coherence tomography(OCT)imaging for high scattering media.The available methods are difficult to remove saturation artifacts and restore texture completely in OCT images.We proposed a deep learning-based inpainting method of saturation artifacts in this paper.The generation mechanism of saturation artifacts was analyzed,and experimental and simulated datasets were built based on the mechanism.Enhanced super-resolution generative adversarial networks were trained by the clear–saturated phantom image pairs.The perfect reconstructed results of experimental zebrafish and thyroid OCT images proved its feasibility,strong generalization,and robustness.
文摘This study addresses challenges in fetal magnetic resonance imaging (MRI) related to motion artifacts, maternal respiration, and hardware limitations. To enhance MRI quality, we employ deep learning techniques, specifically utilizing Cycle GAN. Synthetic pairs of images, simulating artifacts in fetal MRI, are generated to train the model. Our primary contribution is the use of Cycle GAN for fetal MRI restoration, augmented by artificially corrupted data. We compare three approaches (supervised Cycle GAN, Pix2Pix, and Mobile Unet) for artifact removal. Experimental results demonstrate that the proposed supervised Cycle GAN effectively removes artifacts while preserving image details, as validated through Structural Similarity Index Measure (SSIM) and normalized Mean Absolute Error (MAE). The method proves comparable to alternatives but avoids the generation of spurious regions, which is crucial for medical accuracy.
基金supported by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(IITP-2024-RS-2024-00437494)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation).
文摘Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies.
文摘The importance of the accuracy of preparing biological specimen as histological sections that can be examined under a microscope lies in reflecting a true image of the tissue that includes all its components, which are used in scientific research or for the purpose of diagnosing various diseases of the body. Despite this, some cellular structures within the tissue may suffer from some alterations that result from the appearance of defects during any stage of preparing these microscopic sections, which alter or interfere with the precise cellular structures and morphology that constitute the tissue and thus give a different image for tissue features and cause confusion in the work histopathologist in the diagnosis. There are several reasons that can cause a misdiagnosis of the sample that occurs during the surgical separation process or after separation during the stages of microscopic preparation techniques from fixation stage, tissue processing, embedding or microtomy, staining until mounting procedures. The constant need to identify these defects and their causes in addition to try to reduce them is one of the biggest challenges evident in pathology laboratories. Therefore, this study aims to review the most common defects that occur in any stage of tissue processing, with an explanation of their causes and appropriate ways to avoid them.
基金funded by the National Key Research and Development Program of China,No.2022YFB3303303Key Open Fund of State Key Lab of Materials Processing and Die&Mould Technology of China,No.P2024-001Zhejiang Provincial Research and Development Project of China,No.LGG22E050010。
文摘This study presents an energy consumption(EC)forecasting method for laser melting manufacturing of metal artifacts based on fusionable transfer learning(FTL).To predict the EC of manufacturing products,particularly from scale-down to scale-up,a general paradigm was first developed by categorizing the overall process into three main sub-steps.The operating electrical power was further formulated as a combinatorial function,based on which an operator learning network was adopted to fit the nonlinear relations between the fabricating arguments and EC.Parallel-arranged networks were constructed to investigate the impacts of fabrication variables and devices on power.Considering the interconnections among these factors,the outputs of the neural networks were blended and fused to jointly predict the electrical power.Most innovatively,large artifacts can be decomposed into timedependent laser-scanning trajectories,which can be further transformed into fusionable information via neural networks,inspired by large language model.Accordingly,transfer learning can deal with either scale-down or scale-up forecasting,namely,FTL with scalability within artifact structures.The effectiveness of the proposed FTL was verified through physical fabrication experiments via laser powder bed fusion.The relative error of the average and overall EC predictions based on FTL was maintained below 0.83%.The melting fusion quality was examined using metallographic diagrams.The proposed FTL framework can forecast the EC of scaled structures,which is particularly helpful in price estimation and quotation of large metal products towards carbon peaking and carbon neutrality.
文摘This paper proposes a new adaptive post-filtering algorithm to remove coding artifacts in block-based video coder. The proposed method concentrates on blocking and ringing artifacts removal. For de-blocking, the blocking strength is identified to determine the filtering range, and the maximum quantization parameter of the image is used to adapt the 1D fuzzy filter. For de-ringing, besides the edge detection, a complementary ringing detection method is proposed to locate the neglected ringing blocks, and the gradient threshold is adopted to adjust the parameter of 2D fuzzy filter. Experiments are performed on the MPEG-4 sequences. Compared with other methods, the proposed one achieves better detail preservation and artifacts removal performance with lower computational cost.
基金the National Natural Science Foundation of China(No.61874171)the Alibaba Innovative Research Program of Alibaba Group。
文摘Removing different types of artifacts from the electroencephalography(EEG)recordings is a critical step in performing EEG signal analysis and diagnosis.Most of the existing algorithms aim for removing single type of artifacts,leading to a complex system if an EEG recording contains different types of artifacts.With the advancement in wearable technologies,it is necessary to develop an energy-efficient algorithm to deal with different types of artifacts for single-channel wearable EEG devices.In this paper,an automatic EEG artifact removal algorithm is proposed that effectively reduces three types of artifacts,i.e.,ocular artifact(OA),transmission-line/harmonic-wave artifact(TA/HA),and muscle artifact(MA),from a single-channel EEG recording.The effectiveness of the proposed algorithm is verified on both simulated noisy EEG signals and real EEG from CHB-MIT dataset.The experimental results show that the proposed algorithm effectively suppresses OA,MA and TA/HA from a single-channel EEG recording as well as physical movement artifact.
文摘A simulation method is proposed to predict the motion artifacts of plasma display panels （PDPs）. The method simulates the behavior of the human vision system when perceiving moving objects. The simulation is based on the measured temporal light properties of the display for each gray level and each phosphor. Both the effect of subfield arrangement and phosphor decay are involved. A novel algorithm is proposed to improve the calculation speed. The simulation model manages to predict the appearance of the motion image perceived by a human with a still image. The results are validated by a set of perceptual evaluation experiments. This rapid and accurate prediction of motion artifacts enables objective characterization of the PDP performance in this aspect.
基金supported by the National Cancer Institute of the National Institutes of Health under Award No.(R37CA240806).
文摘X-ray-induced acoustic computed tomography(XACT)is a hybrid imaging modality for detecting X-ray absorption distribution via ultrasound emission.It facilitates imaging from a single projection X-ray illumination,thus reducing the radiation exposure and improving imaging speed.Nonuniform detector response caused by the interference between multichannel data acquisition for ring array transducers and amplifier systems yields ring artifacts in the reconstructed XACT images,which compromises the image quality.We propose model-based algorithms for ring artifacts corrected XACT imaging and demonstrate their effcacy on numerical and experimental measurements.The corrected reconstructions indicate significantly reduced ring artifacts as compared to their conventional counterparts.
基金Research reported in this publication was supported by the National Heart,Lung,And Blood Institute of the National Institutes of Health,No.R01HL151561The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
文摘This review paper aims to summarize cardiac CT blooming artifacts,how they present clinically and what their root causes and potential solutions are.A literature survey was performed covering any publications with a specific interest in calcium blooming and stent blooming in cardiac CT.The claims from literature are compared and interpreted,aiming at narrowing down the root causes and most promising solutions for blooming artifacts.More than 30 journal publications were identified with specific relevance to blooming artifacts.The main reported causes of blooming artifacts are the partial volume effect,motion artifacts and beam hardening.The proposed solutions are classified as high-resolution CT hardware,high-resolution CT reconstruction,subtraction techniques and post-processing techniques,with a special emphasis on deep learning(DL)techniques.The partial volume effect is the leading cause of blooming artifacts.The partial volume effect can be minimized by increasing the CT spatial resolution through higherresolution CT hardware or advanced high-resolution CT reconstruction.In addition,DL techniques have shown great promise to correct for blooming artifacts.A combination of these techniques could avoid repeat scans for subtraction techniques.
文摘BACKGROUND Endoscopy artifacts are widespread in real capsule endoscopy(CE)images but not in high-quality standard datasets.AIM To improve the segmentation performance of polyps from CE images with artifacts based on ensemble learning.METHODS We collected 277 polyp images with CE artifacts from 5760 h of videos from 480 patients at Guangzhou First People’s Hospital from January 2016 to December 2019.Two public high-quality standard external datasets were retrieved and used for the comparison experiments.For each dataset,we randomly segmented the data into training,validation,and testing sets for model training,selection,and testing.We compared the performance of the base models and the ensemble model in segmenting polyps from images with artifacts.RESULTS The performance of the semantic segmentation model was affected by artifacts in the sample images,which also affected the results of polyp detection by CE using a single model.The evaluation based on real datasets with artifacts and standard datasets showed that the ensemble model of all state-of-the-art models performed better than the best corresponding base learner on the real dataset with artifacts.Compared with the corresponding optimal base learners,the intersection over union(IoU)and dice of the ensemble learning model increased to different degrees,ranging from 0.08%to 7.01%and 0.61%to 4.93%,respectively.Moreover,in the standard datasets without artifacts,most of the ensemble models were slightly better than the base learner,as demonstrated by the IoU and dice increases ranging from-0.28%to 1.20%and-0.61%to 0.76%,respectively.CONCLUSION Ensemble learning can improve the segmentation accuracy of polyps from CE images with artifacts.Our results demonstrated an improvement in the detection rate of polyps with interference from artifacts.
基金This work was supported by the National Key Research and Development Program of China(2020YFC1512001)the Guangdong Basic and Applied Basic Research Foundation(No.2021A1515011427)+6 种基金the Research Grants Council of the Hong Kong Special Administrative Region(Projects PolyU 152232/17E,PolyU 152164/18Eand PolyU152233/19E)the National NaturalScience Foundation of China(Grants 41790445,41974006,42074040 and 41941019)the Shenzhen Scientific Research and Development Funding Program(Nos.20200807110745001,KQJSCX20180328093453763and20200812164904001)the Department of Education of Guangdong(218KTSCX196)the Fundamental Research Funds for the Central Universities(300102269207)the Research Institute for Sustainable Urban Development(RISUD)(BBWB)the Innovation and Technology Fund of Hong Kong(ITP/019/20LP).
文摘Interferometric synthetic aperture radar(InSAR)has been widely used to measure ground displacements related to geophysical and anthropic activities over the past three decades.Satellite SAR systems use microwave signals that interact with the ionosphere when they travel through it during the imaging processes.In this context,ionospheric variations can significantly contaminate SAR imagery,which in turn affects spaceborne InSAR measurements.This bias also leads to a decrease in the coherence and accuracy of InSAR measurements,especially for the low-frequency SAR systems.In this paper,we give an overview of the latest methods for mitigating the ionospheric contributions in InSAR,including Faraday rotation method,azimuth shift method,and range split-spectrum method,and only focus on the single pair of InSAR interferograms.The current challenges and future perspectives are outlined at the end of this paper.
基金This study was supported by the National Natural Science Foundation of China(Nos.62022037,61775028,81571722,61528401 and 61921002)Guangdong province(2019ZT08Y191)+1 种基金Shenzhen Science and Technology Program(KQTD20190929172743294)Startup grant from Southern University of Science and Technology.
文摘Microwave-induced thermoacoustic imaging(MI-TAI)remains one of the focus of attention among biomedical imaging modalities over the last decade.However,the transmission and dis-tribution of microwave inside bio-tissues are complicated,thus result in severe artifacts.In this study,to reveal the underlying mechanisms of artifacts,we deeply investigate the distribution of specific absorption rate(SAR)inside tissue-mimicking phantoms with varied morphological features using both mathematical simulations and corresponding experiments.Our simulated results,which are confirmed by the associated experimental results,show that the SAR distri-bution highly depends on the geometries of the imaging targets and the polarizing features of the microwave.In addition,we propose the potential mechanisms including Mie-scattering,Fabry-Perot-feature,small curvature effect to interpret the diffraction effect in different scenarios,which may provide basic guidance to predict and distinguish the artifacts for TAI in both fundamental and clinical studies.
基金the Natural Science Foundation of China(Grant Nos.U1532113,11475170,and 11905041)Fundamental Research Funds for the Central Universities(Grant No.PA2020GDKC0024)Anhui Provincial Natural Science Foundation(Grant No.2208085MA18).
文摘X-ray dark-field imaging using a grating interferometer has shown potential benefits for a variety of applications in recent years.X-ray dark-field image is commonly retrieved by using discrete Fourier transform from the acquired phasestepping data.The retrieval process assumes a constant phase step size and a constant flux for each stepped grating position.However,stepping errors and flux fluctuations inevitably occur due to external vibrations and/or thermal drift during data acquisition.Previous studies have shown that those influences introduce errors in the acquired phase-stepping data,which cause obvious moiréartifacts in the retrieved refraction image.This work investigates moiréartifacts in x-ray dark-field imaging as a result of flux fluctuations.For the retrieved mean intensity,amplitude,visibility and dark-field images,the dependence of moiréartifacts on flux fluctuation factors is theoretically derived respectively by using a first-order Taylor series expansion.Results of synchrotron radiation experiments verify the validity of the derived analytical formulas.The spatial frequency characteristics of moiréartifacts are analyzed and compared to those induced by phase-stepping errors.It illustrates that moiréartifacts can be estimated by a weighted mean of flux fluctuation factors,with the weighting factors dependent on the moiréphase and different greatly for each retrieved image.Furthermore,moiréartifacts can even be affected by object’s features not displayed in the particular contrast.These results can be used to interpret images correctly,identify sources of moiréartifacts,and develop dedicated algorithms to remove moiréartifacts in the retrieved multi-contrast images.
基金the National Natural Science Foundation of China,Nos.51935009 and 51821093National key research and development project of China,No.2022YFB3303303+2 种基金Zhejiang University president special fund financed by Zhejiang province,No.2021XZZX008Zhejiang provincial key research and development project of China,Nos.2023C01060,LZY22E060002 and LZ22E050008The Ng Teng Fong Charitable Foundation in the form of ZJU-SUTD IDEA Grant,No.188170-11102.
文摘This study presents a robustness optimization method for rapid prototyping(RP)of functional artifacts based on visualized computing digital twins(VCDT).A generalized multiobjective robustness optimization model for RP of scheme design prototype was first built,where thermal,structural,and multidisciplinary knowledge could be integrated for visualization.To implement visualized computing,the membership function of fuzzy decision-making was optimized using a genetic algorithm.Transient thermodynamic,structural statics,and flow field analyses were conducted,especially for glass fiber composite materials,which have the characteristics of high strength,corrosion resistance,temperature resistance,dimensional stability,and electrical insulation.An electrothermal experiment was performed by measuring the temperature and changes in temperature during RP.Infrared thermographs were obtained using thermal field measurements to determine the temperature distribution.A numerical analysis of a lightweight ribbed ergonomic artifact is presented to illustrate the VCDT.Moreover,manufacturability was verified based on a thermal-solid coupled finite element analysis.The physical experiment and practice proved that the proposed VCDT provided a robust design paradigm for a layered RP between the steady balance of electrothermal regulation and manufacturing efficacy under hybrid uncertainties.
基金This work was supported in part by National Natural Science Foundation of China，National 973 Basic Research Program of China，the Fundamental Research Funds for the Central Universities,HUST
文摘JPEG-Compatibility steganalysis detects the presence of secret message embedded in the JPEG decompressed images and estimates the embedding rate. We propose a JPEG-Compatibility steganalysis algorithm that estimates the embedding rate based on the difference between the stego image and its recompression based predicted co-vet image. In particular, compression artifacts and embedding changes are distinguished based on the amplitude of pixel value changes. This is done independent of the embedding positions, thus is effective for both content non-adaptive and content adaptive steganography. In addition, we also improve the recompression prediction scheme to more accurately estimate the JPEG quantization table. Experimental results show that the proposed algorithm is significantly more effective in detecting spatial ±1 steganography across a wide range of quality factors and embedding rates, when compared to the previous works.
基金the National Key Research and Development Program of China(Grant Nos.2016YFA0401502 and 2017YFB0701903)the National Natural Science Foundation of China(Grant Nos.U1832219 and 12005166)+3 种基金the Youth Innovation Promotion Association,the Chinese Academy of Sciences(CAS)(Grant No.2017023)the Guangdong Natural Science Foundation,China(Grant No.2016A030313129)the Key Research Program of the Institute of Geology&Geophysics,CAS(Grant Nos.IGGCAS-201903 and SZJJ201901)the Key Research Program,CAS(Grant Nos.YJKYYQ20190043,ZDBS-LY-DQC003,XDA14040401,and KFZD-SW-422).
文摘Ring artifacts will happen mostly when the detector has inconsistent response among the detector channels,and the characteristic produced rings centered in the iso-center in the reconstructed slices inevitably affect the recognition and analysis of the corresponding sample structures in neutron computed tomography(CT).In this work,a ring correction method based on the projection-field(RCP)is proposed,it is a pre-processing method and provides the corrected projection data directly,which is also conducive to efficient data storage and other algorithmic researches.Simulation and physical experiments are performed for verifying the effect of the method,and one of the correction methods based on the image-field is used for comparison.The results demonstrate that the RCP can correct the ring artifacts well without reducing the image resolution or over-correction.
