As a pathfinder of the SiTian project,the Mini-SiTian(MST)Array,employed three commercial CMOS cameras,represents a next-generation,cost-effective optical time-domain survey project.This paper focuses primarily on the...As a pathfinder of the SiTian project,the Mini-SiTian(MST)Array,employed three commercial CMOS cameras,represents a next-generation,cost-effective optical time-domain survey project.This paper focuses primarily on the precise data processing pipeline designed for wide-field,CMOS-based devices,including the removal of instrumental effects,astrometry,photometry,and flux calibration.When applying this pipeline to approximately3000 observations taken in the Field 02(f02)region by MST,the results demonstrate a remarkable astrometric precision of approximately 70–80 mas(about 0.1 pixel),an impressive calibration accuracy of approximately1 mmag in the MST zero points,and a photometric accuracy of about 4 mmag for bright stars.Our studies demonstrate that MST CMOS can achieve photometric accuracy comparable to that of CCDs,highlighting the feasibility of large-scale CMOS-based optical time-domain surveys and their potential applications for cost optimization in future large-scale time-domain surveys,like the SiTian project.展开更多
This research aims to define an efficient and fast quantification of bitumen removal on the road surface by Digital Imaging Processing (DIP) and spectral analysis. The retrieval of bitumen removal is an important issu...This research aims to define an efficient and fast quantification of bitumen removal on the road surface by Digital Imaging Processing (DIP) and spectral analysis. The retrieval of bitumen removal is an important issue for road management and environmental studies related to asphalt wear and environmental pollution. The calculation of the Exposed Aggregate Index (EAI), based on DIP, allows to quantify in each frame the superficial removal of bitumen and the exposure of aggregates. A procedure, based on non-parametric classification process of digital images, gives a fast response of EAI. A correlation among EAI and spectral data, between 390 nm and 900 nm range, is evaluated. Results show a good correlation between spectral data at different wavelength and EAI. Finally, this work evaluates the possibility to retrieve asphalt bitumen removal through remote sensed imagery.展开更多
Objective To study the effect of using improved 2D computer-assisted fluoroscopic navigation through simulating 3D vertebrae image to guide pedicle screw internal fixation.Methods Posterior pedicle screw internal fixa...Objective To study the effect of using improved 2D computer-assisted fluoroscopic navigation through simulating 3D vertebrae image to guide pedicle screw internal fixation.Methods Posterior pedicle screw internal fixation,distraction展开更多
The aim of this study was to compare the sperm nuclear and acrosomal morphometry of three species of domestic artiodactyls; cattle （Bos taurus）, sheep （Ovis aries）, and pigs （Sus scrofa）. Semen smears of twenty ...The aim of this study was to compare the sperm nuclear and acrosomal morphometry of three species of domestic artiodactyls; cattle （Bos taurus）, sheep （Ovis aries）, and pigs （Sus scrofa）. Semen smears of twenty ejaculates from each species were fixed and labeled with a propidium iodide-Pisum sativum agglutinin （PI/PSA） combination. Digital images of the sperm nucleus, acrosome, and whole sperm head were captured and analyzed. The use of the PI/PSA combination and CASA-Morph fluorescence-based method allowed the capture, morphometric analysis, and differentiation of most sperm nuclei, acrosomes and whole heads, and the assessment of acrosomal integrity with a high precision in the three species studied. For the size of the head and nuclear area, the relationship between the three species may be summarized as bull 〉 ram 〉 boar. However, for the other morphometric parameters （length, width, and perimeter）, there were differences in the relationships between species for sperm nuclei and whole sperm heads. Bull sperm acrosomes were clearly smaller than those in the other species studied and covered a smaller proportion of the sperm head. The acrosomal morphology, small in the bull, large and broad in the sheep, and large, long, and with a pronounced equatorial segment curve in the boar, was species-characteristic. It was concluded that there are clear variations in the size and shape of the sperm head components between the three species studied, the acrosome being the structure showing the most variability, allowing a clear distinction of the spermatozoa of each species.展开更多
Polygonati rhizoma is often used in Chinese medicine and as food.In this study,atmospheric pressure matrixassisted laser desorption ionization and quadruple-time-of-flight(MALDI-Q-TOF)mass spectrometry techniques were...Polygonati rhizoma is often used in Chinese medicine and as food.In this study,atmospheric pressure matrixassisted laser desorption ionization and quadruple-time-of-flight(MALDI-Q-TOF)mass spectrometry techniques were applied to P.rhizoma samples from Polygonatum cyrtonema Hua species.Positive ions were mainly detected in the mass range of m/z 200-600,while negative ions were mainly observed in the mass range of m/z 100-450.A total of 263 components were identified and the spatial distribution and changes in saccharides contents during the steaming process of P.rhizoma were investigated.Monosaccharide and disaccharide exhibit a relatively uniform distribution,while the oligosaccharides were mainly found in the bast of fresh P.rhizoma.Although the contents of monosaccharide and disaccharide were increased during steaming,that of trisaccharide,tetrasaccharide,and pentasaccharide were decreased.We used the 5 saccharide types with the greatest variation in content as variables for the principal component analysis(PCA)and cluster analysis.Both PCA and cluster analysis showed that these 5 saccharides can be used as markers in the steaming process of the P.rhizoma.Present study of mass spectrometry imaging provides novel insights into the spatiotemporal accumulation patterns of saccharides in P.rhizoma,improving our understanding of the steaming process.展开更多
In micro milling machining,tool wear directly affects workpiece quality and accuracy,making effective tool wear monitoring a key factor in ensuring product integrity.The use of machine vision-based methods can provide...In micro milling machining,tool wear directly affects workpiece quality and accuracy,making effective tool wear monitoring a key factor in ensuring product integrity.The use of machine vision-based methods can provide an intuitive and efficient representation of tool wear conditions.However,micro milling tools have non-flat flanks,thin coatings can peel off,and spindle orientation is uncertain during downtime.These factors result in low pixel values,uneven illumination,and arbitrary tool position.To address this,we propose an image-based tool wear monitoring method.It combines multiple algorithms to restore lost pixels due to uneven illumination during segmentation and accurately extract wear areas.Experimental results demonstrate that the proposed algorithm exhibits high robustness to such images,effectively addressing the effects of illumination and spindle orientation.Additionally,the algorithm has low complexity,fast execution time,and significantly reduces the detection time in situ.展开更多
Global Navigation Satellite System(GNSS)imaging method(GIM)has been successfully applied to global regions to investigate vertical land motion(VLM)of the Earth's surface.GNSS images derived from conventional GIM m...Global Navigation Satellite System(GNSS)imaging method(GIM)has been successfully applied to global regions to investigate vertical land motion(VLM)of the Earth's surface.GNSS images derived from conventional GIM method may present fragmented patches and encounter problems caused by excessive smoothing of velocity peaks,leading to difficulty in short-wavelength deformation detection and improper geophysical interpretation.Therefore,we propose a novel GNSS imaging method based on Gaussian process regression with velocity uncertainty considered(GPR-VU).Gaussian processing regression is introduced to describe the spatial relationship between neighboring site pairs as a priori weights and then reweight velocities by known station uncertainties,converting the discrete velocity field to a continuous one.The GPR-VU method is applied to reconstruct VLM images in the southwestern United States and the eastern Qinghai-Xizang Plateau,China,using the GNSS position time series in vertical direction.Compared to the traditional GIM method,the root-mean-square(RMS)and overall accuracy of the confusion matrix of the GPR-VU method increase by 5.0%and 14.0%from the 1°×1°checkerboard test in the southwestern United States.Similarly,the RMS and overall accuracy increase by 33.7%and 15.8%from the 6°×6°checkerboard test in the eastern Qinghai-Xizang Plateau.These checkerboard tests validate the capability to effectively capture the spatiotemporal variations characteristics of VLM and show that this algorithm outperforms the sparsely distributed network in the Qinghai-Xizang Plateau.The images from the GPR-VU method using real data in both regions show significant subsidence around Lassen Volcanic in northern California within a 30 km radius,slight uplift in the northern Sichuan Basin,and subsidence in its central and southern sections.These results further qualitatively illustrate consistency with previous findings.The GPR-VU method outperforms in diminishing the effect by fragmented patches,excessive smoothing of velocity peaks,and detecting potential short-wavelength deformations.展开更多
Deep learning now underpins many state-of-the-art systems for biomedical image and signal processing,enabling automated lesion detection,physiological monitoring,and therapy planning with accuracy that rivals expert p...Deep learning now underpins many state-of-the-art systems for biomedical image and signal processing,enabling automated lesion detection,physiological monitoring,and therapy planning with accuracy that rivals expert performance.This survey reviews the principal model families as convolutional,recurrent,generative,reinforcement,autoencoder,and transfer-learning approaches as emphasising how their architectural choices map to tasks such as segmentation,classification,reconstruction,and anomaly detection.A dedicated treatment of multimodal fusion networks shows how imaging features can be integrated with genomic profiles and clinical records to yield more robust,context-aware predictions.To support clinical adoption,we outline post-hoc explainability techniques(Grad-CAM,SHAP,LIME)and describe emerging intrinsically interpretable designs that expose decision logic to end users.Regulatory guidance from the U.S.FDA,the European Medicines Agency,and the EU AI Act is summarised,linking transparency and lifecycle-monitoring requirements to concrete development practices.Remaining challenges as data imbalance,computational cost,privacy constraints,and cross-domain generalization are discussed alongside promising solutions such as federated learning,uncertainty quantification,and lightweight 3-D architectures.The article therefore offers researchers,clinicians,and policymakers a concise,practice-oriented roadmap for deploying trustworthy deep-learning systems in healthcare.展开更多
Aconiti Lateralis Radix Praeparata(Fuzi)represents a significant traditional Chinese medicine(TCM)that exhibits both notable pharmacological effects and toxicity.Various processing methods are implemented to reduce th...Aconiti Lateralis Radix Praeparata(Fuzi)represents a significant traditional Chinese medicine(TCM)that exhibits both notable pharmacological effects and toxicity.Various processing methods are implemented to reduce the toxicity of raw Fuzi by modifying its toxic and effective components,primarily diterpenoid alkaloids.To comprehensively analyze the chemical variations between different Fuzi products,ultra-high performance liquid chromatography-linear ion trap quadrupole Orbitrap mass spectrometry(UHPLC-LTQ-Orbitrap MS)was employed to systematically characterize Shengfuzi,Heishunpian and Baifupian.A total of 249 diterpenoid alkaloids present in Shengfuzi were identified,while only 111 and 61 in Heishunpian and Baifupian were detected respectively,indicating substantial differences among these products.An untargeted metabolomics approach combined with multivariate statistical analysis revealed 42 potential chemical markers.Through subsequent validation using 52 batches of commercial Heishunpian and Baifupian samples,8 robust markers distinguishing these products were identified,including AC1-propanoic acid-3OH,HE-glucoside,HE-hydroxyvaleric acid-2OH,dihydrosphingosine,N-dodecoxycarbonylvaline and three unknown compounds.Additionally,the MS imaging(MSI)technique was utilized to visualize the spatial distribution of chemical constituents in raw Fuzi,revealing how different processing procedures affect the chemical variations between Heishunpian and Baifupian.The distribution patterns of different diterpenoid alkaloid subtypes partially explained the chemical differences among products.This research provides valuable insights into the material basis for future investigations of different Fuzi products.展开更多
Parkinson's disease is a neurodegenerative disorder caused by loss of dopamine neurons in the substantia nigra pars compacta. Tremor, rigidity, and bradykinesia are the major symptoms of the disease. These motor i...Parkinson's disease is a neurodegenerative disorder caused by loss of dopamine neurons in the substantia nigra pars compacta. Tremor, rigidity, and bradykinesia are the major symptoms of the disease. These motor impairments are often accompanied by affective and emotional dysfunctions which have been largely studied over the last decade. The aim of this study was to investigate emotional processing organization in the brain of patients with Parkinson's disease and to explore whether there are differences between recognition of different types of emotions in Parkinson's disease. We examined 18 patients with Parkinson's disease(8 men, 10 women) with no history of neurological or psychiatric comorbidities. All these patients underwent identical brain blood oxygenation level-dependent functional magnetic resonance imaging for emotion evaluation. Blood oxygenation level-dependent functional magnetic resonance imaging results revealed that the occipito-temporal cortices, insula, orbitofrontal cortex, basal ganglia, and parietal cortex which are involved in emotion processing, were activated during the functional control. Additionally, positive emotions activate larger volumes of the same anatomical entities than neutral and negative emotions. Results also revealed that Parkinson's disease associated with emotional disorders are increasingly recognized as disabling as classic motor symptoms. These findings help clinical physicians to recognize the emotional dysfunction of patients with Parkinson's disease.展开更多
This paper provides a comprehensive introduction to the mini-Si Tian Real-time Image Processing pipeline(STRIP)and evaluates its operational performance.The STRIP pipeline is specifically designed for real-time alert ...This paper provides a comprehensive introduction to the mini-Si Tian Real-time Image Processing pipeline(STRIP)and evaluates its operational performance.The STRIP pipeline is specifically designed for real-time alert triggering and light curve generation for transient sources.By applying the STRIP pipeline to both simulated and real observational data of the Mini-Si Tian survey,it successfully identified various types of variable sources,including stellar flares,supernovae,variable stars,and asteroids,while meeting requirements of reduction speed within 5 minutes.For the real observational data set,the pipeline detected one flare event,127 variable stars,and14 asteroids from three monitored sky regions.Additionally,two data sets were generated:one,a real-bogus training data set comprising 218,818 training samples,and the other,a variable star light curve data set with 421instances.These data sets will be used to train machine learning algorithms,which are planned for future integration into STRIP.展开更多
Breast cancer remains one of the most pressing global health concerns,and early detection plays a crucial role in improving survival rates.Integrating digital mammography with computational techniques and advanced ima...Breast cancer remains one of the most pressing global health concerns,and early detection plays a crucial role in improving survival rates.Integrating digital mammography with computational techniques and advanced image processing has significantly enhanced the ability to identify abnormalities.However,existing methodologies face persistent challenges,including low image contrast,noise interference,and inaccuracies in segmenting regions of interest.To address these limitations,this study introduces a novel computational framework for analyzing mammographic images,evaluated using the Mammographic Image Analysis Society(MIAS)dataset comprising 322 samples.The proposed methodology follows a structured three-stage approach.Initially,mammographic scans are classified using the Breast Imaging Reporting and Data System(BI-RADS),ensuring systematic and standardized image analysis.Next,the pectoral muscle,which can interfere with accurate segmentation,is effectively removed to refine the region of interest(ROI).The final stage involves an advanced image pre-processing module utilizing Independent Component Analysis(ICA)to enhance contrast,suppress noise,and improve image clarity.Following these enhancements,a robust segmentation technique is employed to delineated abnormal regions.Experimental results validate the efficiency of the proposed framework,demonstrating a significant improvement in the Effective Measure of Enhancement(EME)and a 3 dB increase in Peak Signal-to-Noise Ratio(PSNR),indicating superior image quality.The model also achieves an accuracy of approximately 97%,surpassing contemporary techniques evaluated on the MIAS dataset.Furthermore,its ability to process mammograms across all BI-RADS categories highlights its adaptability and reliability for clinical applications.This study presents an advanced and dependable computational framework for mammographic image analysis,effectively addressing critical challenges in noise reduction,contrast enhancement,and segmentation precision.The proposed approach lays the groundwork for seamless integration into computer-aided diagnostic(CAD)systems,with the potential to significantly enhance early breast cancer detection and contribute to improved patient outcomes.展开更多
In order to study the problem of intelligent information processing in new types of imaging fuze, the method of extracting the invariance features of target images is adopted, and radial basis function neural network ...In order to study the problem of intelligent information processing in new types of imaging fuze, the method of extracting the invariance features of target images is adopted, and radial basis function neural network is used to recognize targets. Owing to its ability of parallel processing, its robustness and generalization, the method can realize the recognition of the conditions of missile-target encounters, and meet the requirements of real-time recognition in the imaging fuze. It is shown that based on artificial neural network target recognition and burst point control are feasible.展开更多
Spatial resolution and image-processing methods for full-field X-ray fluorescence(FF-XRF)imaging using X-ray pinhole cameras were studied using Geant4simulations with different geometries and algorithms for image reco...Spatial resolution and image-processing methods for full-field X-ray fluorescence(FF-XRF)imaging using X-ray pinhole cameras were studied using Geant4simulations with different geometries and algorithms for image reconstruction.The main objectives were:(1)calculating the quantum efficiency curves of specific cameras,(2)studying the relationships between the spatial resolution and the pinhole diameter,magnification,and camera binning value,and(3)comparing image-processing methods for pinhole camera systems.Several results were obtained using a point and plane source as the X-ray fluorescence emitter and an array of 100×100 silicon pixel detectors as the X-ray camera.The quantum efficiency of a back-illuminated deep depletion(BI-DD)structure was above 30%for the XRF energies in the 0.8–9 keV range,with the maximum of 93.7%at 4 keV.The best spatial resolution of the pinhole camera was 24.7μm and 31.3 lp/mm when measured using the profile function of the point source,with the diameter of 20μm,magnification of 3.16,and camera bin of 1.A blind deconvolution algorithm with Gaussian filtering performed better than the Wiener filter and Richardson iterative methods on FF-XRF images,with the signal-to-noise ratio of 7.81 dB and improved signalto-noise ratio of 7.24 dB at the diameter of 120μm,magnification of 1.0,and camera bin of 1.展开更多
Studies concerning phonological processing mainly use written stimuli.Functional magnetic resonance imaging was used to investigate the brain regions related to the phonological processing under the picture stimulus i...Studies concerning phonological processing mainly use written stimuli.Functional magnetic resonance imaging was used to investigate the brain regions related to the phonological processing under the picture stimulus in the rhyme task of Chinese language.Results of the test in 13 healthy college students whose native language is Chinese showed the extensive activation in the frontal lobe,parietal lobe and the occipitotemporal cortex,including the inferior frontal gyrus,middle frontal gyrus,supramarginal gyrus and medial occipitotemporal gyrus under the picture stimuli.Moreover,phonological processing induced activation in the superior temporal gyrus(BA 22)under the picture stimuli,but activation was not found in the middle temporal gyrus.展开更多
Large range cell migration is a severe challenge to imaging algorithm for spaceborne SAR. Based on design of Finite Impulse Response (FIR) filter and Range Doppler (RD) algorithm, a realization of quick-look imaging f...Large range cell migration is a severe challenge to imaging algorithm for spaceborne SAR. Based on design of Finite Impulse Response (FIR) filter and Range Doppler (RD) algorithm, a realization of quick-look imaging for large range cell migration is proposed. It realized quick-look imaging of 8 times reduced resolution with parallel processing on memory shared 8 CPU SGI server. According to simulation experiment, this quick-look imaging algorithm with parallel processing can image 16384x16384 SAR raw data within 6 seconds. It reaches the requirement of real-time imaging.展开更多
Diffraction enhanced imaging （DEI） has been widely applied in many fields, especially when imaging low-Z samples or when the difference in the attenuation coefficient between different regions in the sample is too s...Diffraction enhanced imaging （DEI） has been widely applied in many fields, especially when imaging low-Z samples or when the difference in the attenuation coefficient between different regions in the sample is too small to be detected. Recent developments of this technique have presented a need for a new software package for data analysis. Here, the Diffraction Enhanced Image Reconstructor （DEIReconstructor）, developed in Matlab, is presented. DEIReconstructor has a user-friendly graphical user interface and runs under any of the 32~bit or 64- bit Microsoft Windows operating systems including XP and WinT. Many of its features are integrated to support imaging preprocessing, extract absorption, refractive and scattering information of diffraction enhanced imaging and allow for parallel-beam tomography reconstruction for DEI-CT. Furthermore, many other useful functions are also implemented in order to simplify the data analysis and the presentation of results. The compiled software package is freely available.展开更多
In this paper,a multirate processing approach for microwave imaging is presented.This approach has the advantages of largely compressing the raw spectral data for imaging,greatly reducing the storage requirement and e...In this paper,a multirate processing approach for microwave imaging is presented.This approach has the advantages of largely compressing the raw spectral data for imaging,greatly reducing the storage requirement and enhancing the processing efficiency.To demonstrateits applicability,the proposed approach is tested on both simulated and experimental data.展开更多
A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional（1-D）radar imaging.The coherence between scattering centers is minimized by using spatial smoothing pr...A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional（1-D）radar imaging.The coherence between scattering centers is minimized by using spatial smoothing processing（SSP）.Then the range and polarimetric scattering matrix of the scattering centers are estimated.The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios（SNR）.Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.展开更多
Frame processing method offers a model-based approach to Inverse Synthetic Aperture Radar(ISAR) imaging. It also provides a way to estimate the rotation rate of a non-cooperative target from radar returns via the fram...Frame processing method offers a model-based approach to Inverse Synthetic Aperture Radar(ISAR) imaging. It also provides a way to estimate the rotation rate of a non-cooperative target from radar returns via the frame operator properties. In this paper, the relationship between the best achievable ISAR image and the reconstructed image from radar returns was derived in the framework of Finite Frame Processing theory. We show that image defocusing caused by the use of an incorrect target rotation rate is interpreted under the FP method as a frame operator mismatch problem which causes energy dispersion. The unknown target rotation rate may be computed by optimizing the frame operator via a prominent point. Consequently, a prominent intensity maximization method in FP framework was proposed to estimate the underlying target rotation rate from radar returns. In addition, an image filtering technique was implemented to assist searching for a prominent point in practice. The proposed method is justified via a simulation analysis on the performance of FP imaging versus target rotation rate error.Effectiveness of the proposed method is also confirmed from real ISAR data experiments.展开更多
基金supported by the National Key Basic R&D Program of China via 2023YFA1608303the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0550103)+3 种基金the National Science Foundation of China 12422303,12403024,12222301,12173007,and 12261141690the Postdoctoral Fellowship Program of CPSF under grant Number GZB20240731the Young Data Scientist Project of the National Astronomical Data Center,and the China Post-doctoral Science Foundation No.2023M743447support from the NSFC through grant No.12303039 and No.12261141690.
文摘As a pathfinder of the SiTian project,the Mini-SiTian(MST)Array,employed three commercial CMOS cameras,represents a next-generation,cost-effective optical time-domain survey project.This paper focuses primarily on the precise data processing pipeline designed for wide-field,CMOS-based devices,including the removal of instrumental effects,astrometry,photometry,and flux calibration.When applying this pipeline to approximately3000 observations taken in the Field 02(f02)region by MST,the results demonstrate a remarkable astrometric precision of approximately 70–80 mas(about 0.1 pixel),an impressive calibration accuracy of approximately1 mmag in the MST zero points,and a photometric accuracy of about 4 mmag for bright stars.Our studies demonstrate that MST CMOS can achieve photometric accuracy comparable to that of CCDs,highlighting the feasibility of large-scale CMOS-based optical time-domain surveys and their potential applications for cost optimization in future large-scale time-domain surveys,like the SiTian project.
文摘This research aims to define an efficient and fast quantification of bitumen removal on the road surface by Digital Imaging Processing (DIP) and spectral analysis. The retrieval of bitumen removal is an important issue for road management and environmental studies related to asphalt wear and environmental pollution. The calculation of the Exposed Aggregate Index (EAI), based on DIP, allows to quantify in each frame the superficial removal of bitumen and the exposure of aggregates. A procedure, based on non-parametric classification process of digital images, gives a fast response of EAI. A correlation among EAI and spectral data, between 390 nm and 900 nm range, is evaluated. Results show a good correlation between spectral data at different wavelength and EAI. Finally, this work evaluates the possibility to retrieve asphalt bitumen removal through remote sensed imagery.
文摘Objective To study the effect of using improved 2D computer-assisted fluoroscopic navigation through simulating 3D vertebrae image to guide pedicle screw internal fixation.Methods Posterior pedicle screw internal fixation,distraction
文摘The aim of this study was to compare the sperm nuclear and acrosomal morphometry of three species of domestic artiodactyls; cattle （Bos taurus）, sheep （Ovis aries）, and pigs （Sus scrofa）. Semen smears of twenty ejaculates from each species were fixed and labeled with a propidium iodide-Pisum sativum agglutinin （PI/PSA） combination. Digital images of the sperm nucleus, acrosome, and whole sperm head were captured and analyzed. The use of the PI/PSA combination and CASA-Morph fluorescence-based method allowed the capture, morphometric analysis, and differentiation of most sperm nuclei, acrosomes and whole heads, and the assessment of acrosomal integrity with a high precision in the three species studied. For the size of the head and nuclear area, the relationship between the three species may be summarized as bull 〉 ram 〉 boar. However, for the other morphometric parameters （length, width, and perimeter）, there were differences in the relationships between species for sperm nuclei and whole sperm heads. Bull sperm acrosomes were clearly smaller than those in the other species studied and covered a smaller proportion of the sperm head. The acrosomal morphology, small in the bull, large and broad in the sheep, and large, long, and with a pronounced equatorial segment curve in the boar, was species-characteristic. It was concluded that there are clear variations in the size and shape of the sperm head components between the three species studied, the acrosome being the structure showing the most variability, allowing a clear distinction of the spermatozoa of each species.
基金funded by the Science and Technology Innovation Program of Hunan Province(2022RC1224,2022ZYC010)the Changsha Science and Technology Program(kh2004018)the Training Program for Excellent Young Innovators of Changsha(kq2206064)。
文摘Polygonati rhizoma is often used in Chinese medicine and as food.In this study,atmospheric pressure matrixassisted laser desorption ionization and quadruple-time-of-flight(MALDI-Q-TOF)mass spectrometry techniques were applied to P.rhizoma samples from Polygonatum cyrtonema Hua species.Positive ions were mainly detected in the mass range of m/z 200-600,while negative ions were mainly observed in the mass range of m/z 100-450.A total of 263 components were identified and the spatial distribution and changes in saccharides contents during the steaming process of P.rhizoma were investigated.Monosaccharide and disaccharide exhibit a relatively uniform distribution,while the oligosaccharides were mainly found in the bast of fresh P.rhizoma.Although the contents of monosaccharide and disaccharide were increased during steaming,that of trisaccharide,tetrasaccharide,and pentasaccharide were decreased.We used the 5 saccharide types with the greatest variation in content as variables for the principal component analysis(PCA)and cluster analysis.Both PCA and cluster analysis showed that these 5 saccharides can be used as markers in the steaming process of the P.rhizoma.Present study of mass spectrometry imaging provides novel insights into the spatiotemporal accumulation patterns of saccharides in P.rhizoma,improving our understanding of the steaming process.
基金Supported by National Natural Science Foundation of China(Grant No.52175528)。
文摘In micro milling machining,tool wear directly affects workpiece quality and accuracy,making effective tool wear monitoring a key factor in ensuring product integrity.The use of machine vision-based methods can provide an intuitive and efficient representation of tool wear conditions.However,micro milling tools have non-flat flanks,thin coatings can peel off,and spindle orientation is uncertain during downtime.These factors result in low pixel values,uneven illumination,and arbitrary tool position.To address this,we propose an image-based tool wear monitoring method.It combines multiple algorithms to restore lost pixels due to uneven illumination during segmentation and accurately extract wear areas.Experimental results demonstrate that the proposed algorithm exhibits high robustness to such images,effectively addressing the effects of illumination and spindle orientation.Additionally,the algorithm has low complexity,fast execution time,and significantly reduces the detection time in situ.
基金supported by the National Natural Science Foundation of China(Grant No.42274035)the Major Science and Technology Program for Hubei Province(No.2022AAA002)the Hunan Provincial Land Surveying and Mapping Project(HNGTCH-2023-05)。
文摘Global Navigation Satellite System(GNSS)imaging method(GIM)has been successfully applied to global regions to investigate vertical land motion(VLM)of the Earth's surface.GNSS images derived from conventional GIM method may present fragmented patches and encounter problems caused by excessive smoothing of velocity peaks,leading to difficulty in short-wavelength deformation detection and improper geophysical interpretation.Therefore,we propose a novel GNSS imaging method based on Gaussian process regression with velocity uncertainty considered(GPR-VU).Gaussian processing regression is introduced to describe the spatial relationship between neighboring site pairs as a priori weights and then reweight velocities by known station uncertainties,converting the discrete velocity field to a continuous one.The GPR-VU method is applied to reconstruct VLM images in the southwestern United States and the eastern Qinghai-Xizang Plateau,China,using the GNSS position time series in vertical direction.Compared to the traditional GIM method,the root-mean-square(RMS)and overall accuracy of the confusion matrix of the GPR-VU method increase by 5.0%and 14.0%from the 1°×1°checkerboard test in the southwestern United States.Similarly,the RMS and overall accuracy increase by 33.7%and 15.8%from the 6°×6°checkerboard test in the eastern Qinghai-Xizang Plateau.These checkerboard tests validate the capability to effectively capture the spatiotemporal variations characteristics of VLM and show that this algorithm outperforms the sparsely distributed network in the Qinghai-Xizang Plateau.The images from the GPR-VU method using real data in both regions show significant subsidence around Lassen Volcanic in northern California within a 30 km radius,slight uplift in the northern Sichuan Basin,and subsidence in its central and southern sections.These results further qualitatively illustrate consistency with previous findings.The GPR-VU method outperforms in diminishing the effect by fragmented patches,excessive smoothing of velocity peaks,and detecting potential short-wavelength deformations.
基金supported by the Science Committee of the Ministry of Higher Education and Science of the Republic of Kazakhstan within the framework of grant AP23489899“Applying Deep Learning and Neuroimaging Methods for Brain Stroke Diagnosis”.
文摘Deep learning now underpins many state-of-the-art systems for biomedical image and signal processing,enabling automated lesion detection,physiological monitoring,and therapy planning with accuracy that rivals expert performance.This survey reviews the principal model families as convolutional,recurrent,generative,reinforcement,autoencoder,and transfer-learning approaches as emphasising how their architectural choices map to tasks such as segmentation,classification,reconstruction,and anomaly detection.A dedicated treatment of multimodal fusion networks shows how imaging features can be integrated with genomic profiles and clinical records to yield more robust,context-aware predictions.To support clinical adoption,we outline post-hoc explainability techniques(Grad-CAM,SHAP,LIME)and describe emerging intrinsically interpretable designs that expose decision logic to end users.Regulatory guidance from the U.S.FDA,the European Medicines Agency,and the EU AI Act is summarised,linking transparency and lifecycle-monitoring requirements to concrete development practices.Remaining challenges as data imbalance,computational cost,privacy constraints,and cross-domain generalization are discussed alongside promising solutions such as federated learning,uncertainty quantification,and lightweight 3-D architectures.The article therefore offers researchers,clinicians,and policymakers a concise,practice-oriented roadmap for deploying trustworthy deep-learning systems in healthcare.
基金supported by the Qi-Huang Chief Scientist Program of the National Administration of Traditional Chinese Medicine(2020)the National Key Research and Development Program of China(No.2022YFC3501705)+1 种基金Shanghai Sailing Program(No.23YF1447500)the China Postdoctoral Science Foundation(No.2023M732335).
文摘Aconiti Lateralis Radix Praeparata(Fuzi)represents a significant traditional Chinese medicine(TCM)that exhibits both notable pharmacological effects and toxicity.Various processing methods are implemented to reduce the toxicity of raw Fuzi by modifying its toxic and effective components,primarily diterpenoid alkaloids.To comprehensively analyze the chemical variations between different Fuzi products,ultra-high performance liquid chromatography-linear ion trap quadrupole Orbitrap mass spectrometry(UHPLC-LTQ-Orbitrap MS)was employed to systematically characterize Shengfuzi,Heishunpian and Baifupian.A total of 249 diterpenoid alkaloids present in Shengfuzi were identified,while only 111 and 61 in Heishunpian and Baifupian were detected respectively,indicating substantial differences among these products.An untargeted metabolomics approach combined with multivariate statistical analysis revealed 42 potential chemical markers.Through subsequent validation using 52 batches of commercial Heishunpian and Baifupian samples,8 robust markers distinguishing these products were identified,including AC1-propanoic acid-3OH,HE-glucoside,HE-hydroxyvaleric acid-2OH,dihydrosphingosine,N-dodecoxycarbonylvaline and three unknown compounds.Additionally,the MS imaging(MSI)technique was utilized to visualize the spatial distribution of chemical constituents in raw Fuzi,revealing how different processing procedures affect the chemical variations between Heishunpian and Baifupian.The distribution patterns of different diterpenoid alkaloid subtypes partially explained the chemical differences among products.This research provides valuable insights into the material basis for future investigations of different Fuzi products.
文摘Parkinson's disease is a neurodegenerative disorder caused by loss of dopamine neurons in the substantia nigra pars compacta. Tremor, rigidity, and bradykinesia are the major symptoms of the disease. These motor impairments are often accompanied by affective and emotional dysfunctions which have been largely studied over the last decade. The aim of this study was to investigate emotional processing organization in the brain of patients with Parkinson's disease and to explore whether there are differences between recognition of different types of emotions in Parkinson's disease. We examined 18 patients with Parkinson's disease(8 men, 10 women) with no history of neurological or psychiatric comorbidities. All these patients underwent identical brain blood oxygenation level-dependent functional magnetic resonance imaging for emotion evaluation. Blood oxygenation level-dependent functional magnetic resonance imaging results revealed that the occipito-temporal cortices, insula, orbitofrontal cortex, basal ganglia, and parietal cortex which are involved in emotion processing, were activated during the functional control. Additionally, positive emotions activate larger volumes of the same anatomical entities than neutral and negative emotions. Results also revealed that Parkinson's disease associated with emotional disorders are increasingly recognized as disabling as classic motor symptoms. These findings help clinical physicians to recognize the emotional dysfunction of patients with Parkinson's disease.
基金supported from the Strategic Pioneer Program of the Astronomy Large-Scale Scientific FacilityChinese Academy of Sciences and the Science and Education Integration Funding of University of Chinese Academy of Sciences+9 种基金the supports from the National Key Basic R&D Program of China via 2023YFA1608303the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0550103)the supports from the Strategic Priority Research Program of the Chinese Academy of Sciences under grant No.XDB0550000the National Natural Science Foundation of China(NSFC,grant Nos.12422303 and12261141690)the supports from the NSFC(grant No.12403024)supports from the NSFC through grant Nos.11988101 and 11933004the Postdoctoral Fellowship Program of CPSF under grant No.GZB20240731the Young Data Scientist Project of the National Astronomical Data Centerthe China Post-doctoral Science Foundation(No.2023M743447)supports from the New Cornerstone Science Foundation through the New Cornerstone Investigator Program and the XPLORER PRIZE。
文摘This paper provides a comprehensive introduction to the mini-Si Tian Real-time Image Processing pipeline(STRIP)and evaluates its operational performance.The STRIP pipeline is specifically designed for real-time alert triggering and light curve generation for transient sources.By applying the STRIP pipeline to both simulated and real observational data of the Mini-Si Tian survey,it successfully identified various types of variable sources,including stellar flares,supernovae,variable stars,and asteroids,while meeting requirements of reduction speed within 5 minutes.For the real observational data set,the pipeline detected one flare event,127 variable stars,and14 asteroids from three monitored sky regions.Additionally,two data sets were generated:one,a real-bogus training data set comprising 218,818 training samples,and the other,a variable star light curve data set with 421instances.These data sets will be used to train machine learning algorithms,which are planned for future integration into STRIP.
基金funded by Deanship of Graduate Studies and Scientific Research at Najran University for supporting the research project through the Nama’a program,with the project code NU/GP/MRC/13/771-4.
文摘Breast cancer remains one of the most pressing global health concerns,and early detection plays a crucial role in improving survival rates.Integrating digital mammography with computational techniques and advanced image processing has significantly enhanced the ability to identify abnormalities.However,existing methodologies face persistent challenges,including low image contrast,noise interference,and inaccuracies in segmenting regions of interest.To address these limitations,this study introduces a novel computational framework for analyzing mammographic images,evaluated using the Mammographic Image Analysis Society(MIAS)dataset comprising 322 samples.The proposed methodology follows a structured three-stage approach.Initially,mammographic scans are classified using the Breast Imaging Reporting and Data System(BI-RADS),ensuring systematic and standardized image analysis.Next,the pectoral muscle,which can interfere with accurate segmentation,is effectively removed to refine the region of interest(ROI).The final stage involves an advanced image pre-processing module utilizing Independent Component Analysis(ICA)to enhance contrast,suppress noise,and improve image clarity.Following these enhancements,a robust segmentation technique is employed to delineated abnormal regions.Experimental results validate the efficiency of the proposed framework,demonstrating a significant improvement in the Effective Measure of Enhancement(EME)and a 3 dB increase in Peak Signal-to-Noise Ratio(PSNR),indicating superior image quality.The model also achieves an accuracy of approximately 97%,surpassing contemporary techniques evaluated on the MIAS dataset.Furthermore,its ability to process mammograms across all BI-RADS categories highlights its adaptability and reliability for clinical applications.This study presents an advanced and dependable computational framework for mammographic image analysis,effectively addressing critical challenges in noise reduction,contrast enhancement,and segmentation precision.The proposed approach lays the groundwork for seamless integration into computer-aided diagnostic(CAD)systems,with the potential to significantly enhance early breast cancer detection and contribute to improved patient outcomes.
文摘In order to study the problem of intelligent information processing in new types of imaging fuze, the method of extracting the invariance features of target images is adopted, and radial basis function neural network is used to recognize targets. Owing to its ability of parallel processing, its robustness and generalization, the method can realize the recognition of the conditions of missile-target encounters, and meet the requirements of real-time recognition in the imaging fuze. It is shown that based on artificial neural network target recognition and burst point control are feasible.
基金supported by the Sichuan Science and Technology Program,China(No.2020ZDZX0004)。
文摘Spatial resolution and image-processing methods for full-field X-ray fluorescence(FF-XRF)imaging using X-ray pinhole cameras were studied using Geant4simulations with different geometries and algorithms for image reconstruction.The main objectives were:(1)calculating the quantum efficiency curves of specific cameras,(2)studying the relationships between the spatial resolution and the pinhole diameter,magnification,and camera binning value,and(3)comparing image-processing methods for pinhole camera systems.Several results were obtained using a point and plane source as the X-ray fluorescence emitter and an array of 100×100 silicon pixel detectors as the X-ray camera.The quantum efficiency of a back-illuminated deep depletion(BI-DD)structure was above 30%for the XRF energies in the 0.8–9 keV range,with the maximum of 93.7%at 4 keV.The best spatial resolution of the pinhole camera was 24.7μm and 31.3 lp/mm when measured using the profile function of the point source,with the diameter of 20μm,magnification of 3.16,and camera bin of 1.A blind deconvolution algorithm with Gaussian filtering performed better than the Wiener filter and Richardson iterative methods on FF-XRF images,with the signal-to-noise ratio of 7.81 dB and improved signalto-noise ratio of 7.24 dB at the diameter of 120μm,magnification of 1.0,and camera bin of 1.
基金the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the Key Program of National Social Science Foundation of China in 2010,No.10&ZD126+6 种基金the National Natural Science Foundation of China,No.30740040the National Social Science Foundation of China,No.09CYY016the Humanities and Social Sciences Project of Ministry of Education during the 11th"Five-Year"Plan Period,No.07JA740027the Major Basic Research Program of Natural Science Research of Higher Learning School of Jiangsu Province,No.10KJA180051the Scientific Research Innovation Program for Postgraduate from Higher Learning School of Jiangsu Province in 2009,No.CX09S_011Rthe Key Program of Postgraduate Innovation Engineering of Xuzhou Normal University,No.08YLA003the Key Humanities and Social Sciences Program of Xuzhou Normal University in 2010,No.10SWA06
文摘Studies concerning phonological processing mainly use written stimuli.Functional magnetic resonance imaging was used to investigate the brain regions related to the phonological processing under the picture stimulus in the rhyme task of Chinese language.Results of the test in 13 healthy college students whose native language is Chinese showed the extensive activation in the frontal lobe,parietal lobe and the occipitotemporal cortex,including the inferior frontal gyrus,middle frontal gyrus,supramarginal gyrus and medial occipitotemporal gyrus under the picture stimuli.Moreover,phonological processing induced activation in the superior temporal gyrus(BA 22)under the picture stimuli,but activation was not found in the middle temporal gyrus.
文摘Large range cell migration is a severe challenge to imaging algorithm for spaceborne SAR. Based on design of Finite Impulse Response (FIR) filter and Range Doppler (RD) algorithm, a realization of quick-look imaging for large range cell migration is proposed. It realized quick-look imaging of 8 times reduced resolution with parallel processing on memory shared 8 CPU SGI server. According to simulation experiment, this quick-look imaging algorithm with parallel processing can image 16384x16384 SAR raw data within 6 seconds. It reaches the requirement of real-time imaging.
基金Supported by National Basic Research Program of China(2012CB825800)National Natural Science Foundation of China(11205189,11375225,81271574,U1332109)Knowledge Innovation Program of Chinese Academy of Sciences(KJCX2-YW-N42)
文摘Diffraction enhanced imaging （DEI） has been widely applied in many fields, especially when imaging low-Z samples or when the difference in the attenuation coefficient between different regions in the sample is too small to be detected. Recent developments of this technique have presented a need for a new software package for data analysis. Here, the Diffraction Enhanced Image Reconstructor （DEIReconstructor）, developed in Matlab, is presented. DEIReconstructor has a user-friendly graphical user interface and runs under any of the 32~bit or 64- bit Microsoft Windows operating systems including XP and WinT. Many of its features are integrated to support imaging preprocessing, extract absorption, refractive and scattering information of diffraction enhanced imaging and allow for parallel-beam tomography reconstruction for DEI-CT. Furthermore, many other useful functions are also implemented in order to simplify the data analysis and the presentation of results. The compiled software package is freely available.
文摘In this paper,a multirate processing approach for microwave imaging is presented.This approach has the advantages of largely compressing the raw spectral data for imaging,greatly reducing the storage requirement and enhancing the processing efficiency.To demonstrateits applicability,the proposed approach is tested on both simulated and experimental data.
基金Supported by the National Naturral Science Foundation of China(61301191)
文摘A full-polarimetric super-resolution algorithm with spatial smoothing processing is presented for one-dimensional（1-D）radar imaging.The coherence between scattering centers is minimized by using spatial smoothing processing（SSP）.Then the range and polarimetric scattering matrix of the scattering centers are estimated.The impact of different lengths of the smoothing window on the imaging quality is mainly analyzed with different signal-to-noise ratios（SNR）.Simulation and experimental results show that an improved radar super-resolution range profile and more precise estimation can be obtained by adjusting the length of the smoothing window under different SNR conditions.
基金Partially supported by Australian Air Force Office of Scientific Research(AFOSR)Grant(FA2386-13-1-4080)
文摘Frame processing method offers a model-based approach to Inverse Synthetic Aperture Radar(ISAR) imaging. It also provides a way to estimate the rotation rate of a non-cooperative target from radar returns via the frame operator properties. In this paper, the relationship between the best achievable ISAR image and the reconstructed image from radar returns was derived in the framework of Finite Frame Processing theory. We show that image defocusing caused by the use of an incorrect target rotation rate is interpreted under the FP method as a frame operator mismatch problem which causes energy dispersion. The unknown target rotation rate may be computed by optimizing the frame operator via a prominent point. Consequently, a prominent intensity maximization method in FP framework was proposed to estimate the underlying target rotation rate from radar returns. In addition, an image filtering technique was implemented to assist searching for a prominent point in practice. The proposed method is justified via a simulation analysis on the performance of FP imaging versus target rotation rate error.Effectiveness of the proposed method is also confirmed from real ISAR data experiments.
