Objective To qualitatively assess the diagnostic performance of dynamic contrast enhancement(DCE),diffusionweighted imaging(DWI),and T2-weighted imaging(T2WI),alone or in combination,in the evaluation of breast cancer...Objective To qualitatively assess the diagnostic performance of dynamic contrast enhancement(DCE),diffusionweighted imaging(DWI),and T2-weighted imaging(T2WI),alone or in combination,in the evaluation of breast cancer.Methods We retrospectively reviewed the records of 394 consecutive patients with pathologically confirmed breast lesions who had undergone 3-T magnetic resonance imaging(MRI).The morphological characteristics of breast lesions were evaluated using DCE,DWI,and T2WI based on BI-RADS lexicon descriptors by trained radiologists.Patients were categorized into mass and non-mass groups based on MRI characteristics of the lesions,and the differences between benign and malignant lesions in each group were compared.Clinical prediction models for breast cancer diagnosis were constructed using logistic regression analysis.Diagnostic efficacies were compared using the area under the receiver operating characteristic curve(AUC)and DeLong test.Results For mass-like lesions,all the morphological parameters significantly differentiated benign and malignant lesions on consensus DCE,DWI,and T2WI(P<0.05).The combined method(DCE+DWI+T2WI)had a higher AUC(0.865)than any of the individual modality(DCE:0.786;DWI:0.793;T2WI:0.809)(P<0.05).For non-mass-like lesions,DWI signal intensity was a significant predictor of malignancy(P=0.036),but the model using DWI alone had a low AUC(0.669).Conclusion Morphological assessment using the combination of DCE,DWI,and T2WI provides better diagnostic value in differentiating benign and malignant breast mass-like lesions than assessment with only one of the modalities.展开更多
Airborne area-array whisk-broom imaging systems typically adopt constant-speed scanning schemes.For large-inertia scanning systems,constant-speed scanning requires substantial time to complete the reversal motion,redu...Airborne area-array whisk-broom imaging systems typically adopt constant-speed scanning schemes.For large-inertia scanning systems,constant-speed scanning requires substantial time to complete the reversal motion,reducing the system's adaptability to high-speed reversal scanning and decreasing scanning efficiency.This study proposes a novel sinusoidal variable-speed roll scanning strategy,which reduces abrupt changes in speed and acceleration,minimizing time loss during reversals.Based on the forward image motion compensation strategy in the pitch direction,we establish a line-of-sight(LOS)position calculation model with vertical flight path correction(VFPC),ensuring that the central LOS of the scanned image remains stable on the same horizontal line,facilitating accurate image stitching in whisk-broom imaging.Through theoretical analysis and simulation experiments,the proposed method improves the scanning efficiency by approximately 18.6%at a 90o whiskbroom imaging angle under the same speed height ratio conditions.The new VFPC method enables wide-field,high-resolution imaging,achieving single-line LOS horizontal stability with an accuracy of better than O.4 mrad.The research is of great significance to promote the further development of airborne area-array whisk-broom imaging technology toward wider fields of view,higher speed height ratios,and greater scanning efficiency.展开更多
Manganese(Mn),an essential trace element in the human body,plays critical roles in many biological processes.Recent studies have discovered that Mn^(2+)may promote or directly activate the cGAS-STING pathway,thereby s...Manganese(Mn),an essential trace element in the human body,plays critical roles in many biological processes.Recent studies have discovered that Mn^(2+)may promote or directly activate the cGAS-STING pathway,thereby subsequently initiating the natural immune response and augmenting antitumor therapy.However,the current lack of accurate methods for Mn^(2+)determination in cells significantly limits their mechanism investigation;hence,it is urgent to establish novel tools to detect Mn^(2+)in cells.In this study,the dual-emission carbon dots were initially synthesized via the one-pot hydrothermal method employing L-aspartic acid and p-phenylenediamine as raw materials.In the presence of Mn^(2+),the emission peak centered at 350 nm exhibited significant enhancement,whereas another peak at 610 nm remained stable.Consequently,a ratiometric sensor for Mn^(2+)determination was established using the signal at 350 nm as the responsive signal and the signal at 610 nm as an internal reference.Under the optimal condition,a good linear relationship was achieved between the F350/F610 value and Mn^(2+)concentration ranging from 0.9 to 15μmol/L,with a calculated LOD of 61 nmol/L.Benefiting from the special Mn^(2+)-induced ratiometric approach,this method demonstrates outstanding sensitivity,selectivity,and stability,rendering it applicable for Mn^(2+)determination in complex biological samples,as well as Mn^(2+)imaging in MKN-45 and LO2 cells.展开更多
Tin-lead(Sn-Pb)mixed perovskites are extensively investigated in near-infrared(NIR)photodetectors(PDs)owing to their excellent photoelectric performance.However,achieving high-performance Sn-Pb mixed PDs remains chall...Tin-lead(Sn-Pb)mixed perovskites are extensively investigated in near-infrared(NIR)photodetectors(PDs)owing to their excellent photoelectric performance.However,achieving high-performance Sn-Pb mixed PDs remains challenging,primarily because of the rapid crystallization and the susceptibility of Sn^(2+) to oxidation.To ad⁃dress these issues,this study introduces the multifunctional molecules 2,3-difluorobenzenamine(DBM)to modulate the crystallization of Sn-Pb mixed perovskites and retard the oxidation of Sn^(2+),thereby significantly enhancing film quality.Compared with the pristine film,Sn-Pb mixed perovskite films modulated by DBM molecules exhibit a high⁃ly homogeneous morphology,reduced roughness and defect density.The self-powered NIR PDs fabricated with the improved films have a spectral response range from 300 nm to 1100 nm,a peak responsivity of 0.51 A·W^(-1),a spe⁃cific detectivity as high as 2.46×10^(11)Jones within the NIR region(780 nm to 1100 nm),a linear dynamic range ex⁃ceeding 152 dB,and ultrafast rise/fall time of 123/464 ns.Thanks to the outstanding performance of PDs,the fabri⁃cated 5×5 PDs array demonstrates superior imaging ability in the NIR region up to 980 nm.This work advances the development of Sn-Pb mixed perovskites for NIR detection and paves the way for their commercialization.展开更多
Ischemia is a significant factor affecting the repair of peripheral nerve injuries,while exosomes have been shown to promote angiogenesis.To further investigate the detailed processes and efficacy of exosome thera⁃py ...Ischemia is a significant factor affecting the repair of peripheral nerve injuries,while exosomes have been shown to promote angiogenesis.To further investigate the detailed processes and efficacy of exosome thera⁃py for ischemic peripheral nerve injuries,this study utilized glucose-modified near-infrared-II(NIR-II)quantum dots(QDs)to label adipose-derived stem cell exosomes(QDs-ADSC-Exos),enabling long-term in vivo NIR-II imaging of exosome treatment for ischemic peripheral nerve damage.Experimental results confirmed that QDs can be used for non-invasive in vitro labeling of exosomes,with QDs-ADSC-Exos exhibiting strong fluorescence signals in the NIR-II window and demonstrating favorable NIR-II imaging characteristics in vivo.Notably,QDsADSC-Exos showed accumulation at the site of nerve injury in cases of ischemic peripheral nerve damage.Func⁃tional neurological assessments indicated that QDs-ADSC-Exos effectively promoted neural regeneration.This study highlights the potential of exosomes in treating ischemic peripheral nerve injuries and elucidates the spatio⁃temporal characteristics of exosome therapy,providing objective evidence for the further optimization of exosomebased treatment protocols.展开更多
Using 2-dicyanomethylene-3-cyano-4,5,5-trimethyl-2,5-dihydrofuran(TCF)as a near-infrared fluorescent chromophore,we designed and synthesized a TCF-based fluorescent probe TCF-NS by introducing 2,4-dinitrophenyl ether ...Using 2-dicyanomethylene-3-cyano-4,5,5-trimethyl-2,5-dihydrofuran(TCF)as a near-infrared fluorescent chromophore,we designed and synthesized a TCF-based fluorescent probe TCF-NS by introducing 2,4-dinitrophenyl ether as the recognized site for H_(2)S.The probe TCF-NS displayed a rapid-response fluorescent against H_(2)S with high sensitivity and selection but had no significant fluorescence response to other biothiols.Furthermore,TCF-NS was applied to sense H_(2)S in living cells successfully with minimized cytotoxicity and a large Stokes shift.展开更多
Malignant tumours always threaten human health.For tumour diagnosis,positron emission tomography(PET)is the most sensitive and advanced imaging technique by radiotracers,such as radioactive^(18)F,^(11)C,^(64)Cu,^(68)G...Malignant tumours always threaten human health.For tumour diagnosis,positron emission tomography(PET)is the most sensitive and advanced imaging technique by radiotracers,such as radioactive^(18)F,^(11)C,^(64)Cu,^(68)Ga,and^(89)Zr.Among the radiotracers,the radioactive^(18)F-labelled chemical agent as PET probes plays a predominant role in monitoring,detecting,treating,and predicting tumours due to its perfect half-life.In this paper,the^(18)F-labelled chemical materials as PET probes are systematically summarized.First,we introduce various radionuclides of PET and elaborate on the mechanism of PET imaging.It highlights the^(18)F-labelled chemical agents used as PET probes,including[^(18)F]-2-deoxy-2-[^(18)F]fluoro-D-glucose([^(18)F]-FDG),^(18)F-labelled amino acids,^(18)F-labelled nucleic acids,^(18)F-labelled receptors,^(18)F-labelled reporter genes,and^(18)F-labelled hypoxia agents.In addition,some PET probes with metal as a supplementary element are introduced briefly.Meanwhile,the^(18)F-labelled nanoparticles for the PET probe and the multi-modality imaging probe are summarized in detail.The approach and strategies for the fabrication of^(18)F-labelled PET probes are also described briefly.The future development of the PET probe is also prospected.The development and application of^(18)F-labelled PET probes will expand our knowledge and shed light on the diagnosis and theranostics of tumours.展开更多
The reverse design of solid rocket motor(SRM)propellant grain involves determining the grain geometry to closely match a predefined internal ballistic curve.While existing reverse design methods are feasible,they ofte...The reverse design of solid rocket motor(SRM)propellant grain involves determining the grain geometry to closely match a predefined internal ballistic curve.While existing reverse design methods are feasible,they often face challenges such as lengthy computation times and limited accuracy.To achieve rapid and accurate matching between the targeted ballistic curve and complex grain shape,this paper proposes a novel reverse design method for SRM propellant grain based on time-series data imaging and convolutional neural network(CNN).First,a finocyl grain shape-internal ballistic curve dataset is created using parametric modeling techniques to comprehensively cover the design space.Next,the internal ballistic time-series data is encoded into three-channel images,establishing a potential relationship between the ballistic curves and their image representations.A CNN is then constructed and trained using these encoded images.Once trained,the model enables efficient inference of propellant grain dimensions from a target internal ballistic curve.This paper conducts comparative experiments across various neural network models,validating the effectiveness of the feature extraction method that transforms internal ballistic time-series data into images,as well as its generalization capability across different CNN architectures.Ignition tests were performed based on the predicted propellant grain.The results demonstrate that the relative error between the experimental internal ballistic curves and the target curves is less than 5%,confirming the validity and feasibility of the proposed reverse design methodology.展开更多
Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the phy...Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.展开更多
Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging alo...Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging along a predetermined trajectory.However,SSS images often suffer from speckle noise caused by mutual interference between echoes,and limited AUV computational resources further hinder noise suppression.Existing approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain knowledge.To address the problem,Rep DNet,a novel and effective despeckling convolutional neural network is proposed.Rep DNet introduces two re-parameterized blocks:the Pixel Smoothing Block(PSB)and Edge Enhancement Block(EEB),preserving edge information while attenuating speckle noise.During training,PSB and EEB manifest as double-layered multi-branch structures,integrating first-order and secondorder derivatives and smoothing functions.During inference,the branches are re-parameterized into a 3×3 convolution,enabling efficient inference without sacrificing accuracy.Rep DNet comprises three computational operations:3×3 convolution,element-wise summation and Rectified Linear Unit activation.Evaluations on benchmark datasets,a real SSS dataset and Data collected at Lake Mulan aestablish Rep DNet as a well-balanced network,meeting the AUV computational constraints in terms of performance and latency.展开更多
Objective To observe the cervical elasticity of healthy adult nulliparous women at different age groups and different stages of menstrual cycle with E-Cervix imaging technology.Methods A total of 218 healthy adult nul...Objective To observe the cervical elasticity of healthy adult nulliparous women at different age groups and different stages of menstrual cycle with E-Cervix imaging technology.Methods A total of 218 healthy adult nulliparous women who underwent transvaginal ultrasound examination for routine physical examination were retrospectively enrolled,including 103 in follicular phase,78 in ovulation phase and 37 in luteal phase.Cervical canal length(CL)and E-Cervix elasticity parameters were compared among different age groups and different stages of menstrual cycle,including elasticity contrast index(ECI),hardness ratio(HR),cervical internal and external orifice strain values(IOS and EOS)and IOS/EOS ratio.Results No significant difference of CL nor cervical elasticity parameters was detected among healthy adult nulliparous women at different age groups(all P>0.05).There were significant differences of ECI,HR and IOS among different menstrual cycle stages(all P<0.05),among which women in follicular phase had higher ECI and IOS but lower HR than those in luteal phase(all P<0.05).Conclusion No significant difference of cervical elasticity existed among healthy adult nulliparous women at different age groups.Meanwhile,cervical elasticity of healthy adult nulliparous women changed during menstrual cycle,in follicular phase had higher ECI and IOS but lower HR than in luteal phase.展开更多
The encoding aperture snapshot spectral imaging system,based on the compressive sensing theory,can be regarded as an encoder,which can efficiently obtain compressed two-dimensional spectral data and then decode it int...The encoding aperture snapshot spectral imaging system,based on the compressive sensing theory,can be regarded as an encoder,which can efficiently obtain compressed two-dimensional spectral data and then decode it into three-dimensional spectral data through deep neural networks.However,training the deep neural net⁃works requires a large amount of clean data that is difficult to obtain.To address the problem of insufficient training data for deep neural networks,a self-supervised hyperspectral denoising neural network based on neighbor⁃hood sampling is proposed.This network is integrated into a deep plug-and-play framework to achieve self-supervised spectral reconstruction.The study also examines the impact of different noise degradation models on the fi⁃nal reconstruction quality.Experimental results demonstrate that the self-supervised learning method enhances the average peak signal-to-noise ratio by 1.18 dB and improves the structural similarity by 0.009 compared with the supervised learning method.Additionally,it achieves better visual reconstruction results.展开更多
The geometric accuracy of topographic mapping with high-resolution remote sensing images is inevita-bly affected by the orbiter attitude jitter.Therefore,it is necessary to conduct preliminary research on the stereo m...The geometric accuracy of topographic mapping with high-resolution remote sensing images is inevita-bly affected by the orbiter attitude jitter.Therefore,it is necessary to conduct preliminary research on the stereo mapping camera equipped on lunar orbiter before launching.In this work,an imaging simulation method consid-ering the attitude jitter is presented.The impact analysis of different attitude jitter on terrain undulation is conduct-ed by simulating jitter at three attitude angles,respectively.The proposed simulation method is based on the rigor-ous sensor model,using the lunar digital elevation model(DEM)and orthoimage as reference data.The orbit and attitude of the lunar stereo mapping camera are simulated while considering the attitude jitter.Two-dimensional simulated stereo images are generated according to the position and attitude of the orbiter in a given orbit.Experi-mental analyses were conducted by the DEM with the simulated stereo image.The simulation imaging results demonstrate that the proposed method can ensure imaging efficiency without losing the accuracy of topographic mapping.The effect of attitude jitter on the stereo mapping accuracy of the simulated images was analyzed through a DEM comparison.展开更多
This paper investigates a new vortex wave imaging approach to improve the imaging quality of small metal targets of size less than 1.5 mm.Antennas with different spiral phase plates are designed to efficiently transmi...This paper investigates a new vortex wave imaging approach to improve the imaging quality of small metal targets of size less than 1.5 mm.Antennas with different spiral phase plates are designed to efficiently transmit vortex beams with orbital angular momentums(OAMs).By analyzing the OAM spectrum of the target,it was discovered that the predominant reflection contains a particular OAM mode that carries abundant azimuthal information.This can be explained by the OAM selectivity of the target and the guidance of the vortex transmitting beam.A simple reflection vortex imaging system was designed to capture the phase information.Measurement results show that the high image contrast reaches 14.9%,which is twice as high as that of the imaging without OAM.Both of simulations and experiments demonstrate that the vortex phase imaging approach proposed in this paper can effectively improve the imaging quality at 80 GHz.This approach is suitable for other millimeter wave imaging systems and is helpful to improve the resolution in anti-terrorism security checks.展开更多
The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method f...The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.展开更多
In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantl...In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantly degrades image quality.Traditional denoising methods,typically based on filter techniques,often face challenges related to inefficiency and limited adaptability.To address these limitations,this study proposes a novel SAR image denoising algorithm based on an enhanced residual network architecture,with the objective of enhancing the utility of SAR imagery in complex electromagnetic environments.The proposed algorithm integrates residual network modules,which directly process the noisy input images to generate denoised outputs.This approach not only reduces computational complexity but also mitigates the difficulties associated with model training.By combining the Transformer module with the residual block,the algorithm enhances the network's ability to extract global features,offering superior feature extraction capabilities compared to CNN-based residual modules.Additionally,the algorithm employs the adaptive activation function Meta-ACON,which dynamically adjusts the activation patterns of neurons,thereby improving the network's feature extraction efficiency.The effectiveness of the proposed denoising method is empirically validated using real SAR images from the RSOD dataset.The proposed algorithm exhibits remarkable performance in terms of EPI,SSIM,and ENL,while achieving a substantial enhancement in PSNR when compared to traditional and deep learning-based algorithms.The PSNR performance is enhanced by over twofold.Moreover,the evaluation of the MSTAR SAR dataset substantiates the algorithm's robustness and applicability in SAR denoising tasks,with a PSNR of 25.2021 being attained.These findings underscore the efficacy of the proposed algorithm in mitigating speckle noise while preserving critical features in SAR imagery,thereby enhancing its quality and usability in practical scenarios.展开更多
Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual...Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual perception,significantly increasing the utility of low-resolution images.In this study,an improved image superresolution reconstruction model based on Generative Adversarial Networks(SRGAN)was proposed.This model introduced a channel and spatial attention mechanism(CSAB)in the generator,allowing it to effectively leverage the information from the input image to enhance feature representations and capture important details.The discriminator was designed with an improved PatchGAN architecture,which more accurately captured local details and texture information of the image.With these enhanced generator and discriminator architectures and an optimized loss function design,this method demonstrated superior performance in image quality assessment metrics.Experimental results showed that this model outperforms traditional methods,presenting more detailed and realistic image details in the visual effects.展开更多
Low-light image enhancement is one of the most active research areas in the field of computer vision in recent years.In the low-light image enhancement process,loss of image details and increase in noise occur inevita...Low-light image enhancement is one of the most active research areas in the field of computer vision in recent years.In the low-light image enhancement process,loss of image details and increase in noise occur inevitably,influencing the quality of enhanced images.To alleviate this problem,a low-light image enhancement model called RetinexNet model based on Retinex theory was proposed in this study.The model was composed of an image decomposition module and a brightness enhancement module.In the decomposition module,a convolutional block attention module(CBAM)was incorporated to enhance feature representation capacity of the network,focusing on crucial features and suppressing irrelevant ones.A multifeature fusion denoising module was designed within the brightness enhancement module,circumventing the issue of feature loss during downsampling.The proposed model outperforms the existing algorithms in terms of PSNR and SSIM metrics on the publicly available datasets LOL and MIT-Adobe FiveK,as well as gives superior results in terms of NIQE metrics on the publicly available dataset LIME.展开更多
In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research direction.The ultimate goal...In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research direction.The ultimate goal is to reduce computational and storage requirements while ensuring detection accuracy and reliability,making it an ideal choice for achieving rapid response and efficient processing.In this regard,a lightweight SAR ship target detection algorithm based on YOLOv8 was proposed in this study.Firstly,the C2f-Sc module was designed by fusing the C2f in the backbone network with the ScConv to reduce spatial redundancy and channel redundancy between features in convolutional neural networks.At the same time,the Ghost module was introduced into the neck network to effectively reduce model parameters and computational complexity.A relatively lightweight EMA attention mechanism was added to the neck network to promote the effective fusion of features at different levels.Experimental results showed that the Parameters and GFLOPs of the improved model are reduced by 8.5%and 7.0%when mAP@0.5 and mAP@0.5:0.95 are increased by 0.7%and 1.8%,respectively.It makes the model lightweight and improves the detection accuracy,which has certain application value.展开更多
文摘Objective To qualitatively assess the diagnostic performance of dynamic contrast enhancement(DCE),diffusionweighted imaging(DWI),and T2-weighted imaging(T2WI),alone or in combination,in the evaluation of breast cancer.Methods We retrospectively reviewed the records of 394 consecutive patients with pathologically confirmed breast lesions who had undergone 3-T magnetic resonance imaging(MRI).The morphological characteristics of breast lesions were evaluated using DCE,DWI,and T2WI based on BI-RADS lexicon descriptors by trained radiologists.Patients were categorized into mass and non-mass groups based on MRI characteristics of the lesions,and the differences between benign and malignant lesions in each group were compared.Clinical prediction models for breast cancer diagnosis were constructed using logistic regression analysis.Diagnostic efficacies were compared using the area under the receiver operating characteristic curve(AUC)and DeLong test.Results For mass-like lesions,all the morphological parameters significantly differentiated benign and malignant lesions on consensus DCE,DWI,and T2WI(P<0.05).The combined method(DCE+DWI+T2WI)had a higher AUC(0.865)than any of the individual modality(DCE:0.786;DWI:0.793;T2WI:0.809)(P<0.05).For non-mass-like lesions,DWI signal intensity was a significant predictor of malignancy(P=0.036),but the model using DWI alone had a low AUC(0.669).Conclusion Morphological assessment using the combination of DCE,DWI,and T2WI provides better diagnostic value in differentiating benign and malignant breast mass-like lesions than assessment with only one of the modalities.
基金Supported by the National Key Research and Development Program(2023YFC3107602)。
文摘Airborne area-array whisk-broom imaging systems typically adopt constant-speed scanning schemes.For large-inertia scanning systems,constant-speed scanning requires substantial time to complete the reversal motion,reducing the system's adaptability to high-speed reversal scanning and decreasing scanning efficiency.This study proposes a novel sinusoidal variable-speed roll scanning strategy,which reduces abrupt changes in speed and acceleration,minimizing time loss during reversals.Based on the forward image motion compensation strategy in the pitch direction,we establish a line-of-sight(LOS)position calculation model with vertical flight path correction(VFPC),ensuring that the central LOS of the scanned image remains stable on the same horizontal line,facilitating accurate image stitching in whisk-broom imaging.Through theoretical analysis and simulation experiments,the proposed method improves the scanning efficiency by approximately 18.6%at a 90o whiskbroom imaging angle under the same speed height ratio conditions.The new VFPC method enables wide-field,high-resolution imaging,achieving single-line LOS horizontal stability with an accuracy of better than O.4 mrad.The research is of great significance to promote the further development of airborne area-array whisk-broom imaging technology toward wider fields of view,higher speed height ratios,and greater scanning efficiency.
基金Supported by National Natural Science Foundation of China(22264023)Natural Science Foundation of Shaanxi Province(2024JC-YBQN-0150)+2 种基金Yan'an Science and Technology Bureau Project(2023-SFGG-057)Scientific Research Projects of Education Department of Shaanxi Province(22JK0614)PhD Start Fund of Yan'an University(YDBK2022-15)。
文摘Manganese(Mn),an essential trace element in the human body,plays critical roles in many biological processes.Recent studies have discovered that Mn^(2+)may promote or directly activate the cGAS-STING pathway,thereby subsequently initiating the natural immune response and augmenting antitumor therapy.However,the current lack of accurate methods for Mn^(2+)determination in cells significantly limits their mechanism investigation;hence,it is urgent to establish novel tools to detect Mn^(2+)in cells.In this study,the dual-emission carbon dots were initially synthesized via the one-pot hydrothermal method employing L-aspartic acid and p-phenylenediamine as raw materials.In the presence of Mn^(2+),the emission peak centered at 350 nm exhibited significant enhancement,whereas another peak at 610 nm remained stable.Consequently,a ratiometric sensor for Mn^(2+)determination was established using the signal at 350 nm as the responsive signal and the signal at 610 nm as an internal reference.Under the optimal condition,a good linear relationship was achieved between the F350/F610 value and Mn^(2+)concentration ranging from 0.9 to 15μmol/L,with a calculated LOD of 61 nmol/L.Benefiting from the special Mn^(2+)-induced ratiometric approach,this method demonstrates outstanding sensitivity,selectivity,and stability,rendering it applicable for Mn^(2+)determination in complex biological samples,as well as Mn^(2+)imaging in MKN-45 and LO2 cells.
基金Supported by National Key Research and Development Program of China(2022YFA1404201)National Natural Science Foundation of China(62205187,U23A20380,U22A2091,62222509,62127817,62075120)+3 种基金Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China(IRT_17R70)Fundamental Research Program of Shanxi Province(202103021223032,202303021222031)Project Funded by China Postdoctoral Science Foundation(2022M722006)Fund for Shanxi“1331 Project”Key Subjects Construction。
文摘Tin-lead(Sn-Pb)mixed perovskites are extensively investigated in near-infrared(NIR)photodetectors(PDs)owing to their excellent photoelectric performance.However,achieving high-performance Sn-Pb mixed PDs remains challenging,primarily because of the rapid crystallization and the susceptibility of Sn^(2+) to oxidation.To ad⁃dress these issues,this study introduces the multifunctional molecules 2,3-difluorobenzenamine(DBM)to modulate the crystallization of Sn-Pb mixed perovskites and retard the oxidation of Sn^(2+),thereby significantly enhancing film quality.Compared with the pristine film,Sn-Pb mixed perovskite films modulated by DBM molecules exhibit a high⁃ly homogeneous morphology,reduced roughness and defect density.The self-powered NIR PDs fabricated with the improved films have a spectral response range from 300 nm to 1100 nm,a peak responsivity of 0.51 A·W^(-1),a spe⁃cific detectivity as high as 2.46×10^(11)Jones within the NIR region(780 nm to 1100 nm),a linear dynamic range ex⁃ceeding 152 dB,and ultrafast rise/fall time of 123/464 ns.Thanks to the outstanding performance of PDs,the fabri⁃cated 5×5 PDs array demonstrates superior imaging ability in the NIR region up to 980 nm.This work advances the development of Sn-Pb mixed perovskites for NIR detection and paves the way for their commercialization.
基金Supported by the National Natural Science Foundation of China(82371373,W2412120)the Shanghai Natural Science Foundation(21ZR1436100).
文摘Ischemia is a significant factor affecting the repair of peripheral nerve injuries,while exosomes have been shown to promote angiogenesis.To further investigate the detailed processes and efficacy of exosome thera⁃py for ischemic peripheral nerve injuries,this study utilized glucose-modified near-infrared-II(NIR-II)quantum dots(QDs)to label adipose-derived stem cell exosomes(QDs-ADSC-Exos),enabling long-term in vivo NIR-II imaging of exosome treatment for ischemic peripheral nerve damage.Experimental results confirmed that QDs can be used for non-invasive in vitro labeling of exosomes,with QDs-ADSC-Exos exhibiting strong fluorescence signals in the NIR-II window and demonstrating favorable NIR-II imaging characteristics in vivo.Notably,QDsADSC-Exos showed accumulation at the site of nerve injury in cases of ischemic peripheral nerve damage.Func⁃tional neurological assessments indicated that QDs-ADSC-Exos effectively promoted neural regeneration.This study highlights the potential of exosomes in treating ischemic peripheral nerve injuries and elucidates the spatio⁃temporal characteristics of exosome therapy,providing objective evidence for the further optimization of exosomebased treatment protocols.
基金financially supported by the Natural Science Foundation of Jiangsu Province(Grant No.BK20241181)the State Key Laboratory of AnalyticalChemistry for Life Science,School of Chemistry and Chemical Engineering,Nanjing University(Grant No.SKLACLS2419)。
文摘Using 2-dicyanomethylene-3-cyano-4,5,5-trimethyl-2,5-dihydrofuran(TCF)as a near-infrared fluorescent chromophore,we designed and synthesized a TCF-based fluorescent probe TCF-NS by introducing 2,4-dinitrophenyl ether as the recognized site for H_(2)S.The probe TCF-NS displayed a rapid-response fluorescent against H_(2)S with high sensitivity and selection but had no significant fluorescence response to other biothiols.Furthermore,TCF-NS was applied to sense H_(2)S in living cells successfully with minimized cytotoxicity and a large Stokes shift.
文摘Malignant tumours always threaten human health.For tumour diagnosis,positron emission tomography(PET)is the most sensitive and advanced imaging technique by radiotracers,such as radioactive^(18)F,^(11)C,^(64)Cu,^(68)Ga,and^(89)Zr.Among the radiotracers,the radioactive^(18)F-labelled chemical agent as PET probes plays a predominant role in monitoring,detecting,treating,and predicting tumours due to its perfect half-life.In this paper,the^(18)F-labelled chemical materials as PET probes are systematically summarized.First,we introduce various radionuclides of PET and elaborate on the mechanism of PET imaging.It highlights the^(18)F-labelled chemical agents used as PET probes,including[^(18)F]-2-deoxy-2-[^(18)F]fluoro-D-glucose([^(18)F]-FDG),^(18)F-labelled amino acids,^(18)F-labelled nucleic acids,^(18)F-labelled receptors,^(18)F-labelled reporter genes,and^(18)F-labelled hypoxia agents.In addition,some PET probes with metal as a supplementary element are introduced briefly.Meanwhile,the^(18)F-labelled nanoparticles for the PET probe and the multi-modality imaging probe are summarized in detail.The approach and strategies for the fabrication of^(18)F-labelled PET probes are also described briefly.The future development of the PET probe is also prospected.The development and application of^(18)F-labelled PET probes will expand our knowledge and shed light on the diagnosis and theranostics of tumours.
文摘The reverse design of solid rocket motor(SRM)propellant grain involves determining the grain geometry to closely match a predefined internal ballistic curve.While existing reverse design methods are feasible,they often face challenges such as lengthy computation times and limited accuracy.To achieve rapid and accurate matching between the targeted ballistic curve and complex grain shape,this paper proposes a novel reverse design method for SRM propellant grain based on time-series data imaging and convolutional neural network(CNN).First,a finocyl grain shape-internal ballistic curve dataset is created using parametric modeling techniques to comprehensively cover the design space.Next,the internal ballistic time-series data is encoded into three-channel images,establishing a potential relationship between the ballistic curves and their image representations.A CNN is then constructed and trained using these encoded images.Once trained,the model enables efficient inference of propellant grain dimensions from a target internal ballistic curve.This paper conducts comparative experiments across various neural network models,validating the effectiveness of the feature extraction method that transforms internal ballistic time-series data into images,as well as its generalization capability across different CNN architectures.Ignition tests were performed based on the predicted propellant grain.The results demonstrate that the relative error between the experimental internal ballistic curves and the target curves is less than 5%,confirming the validity and feasibility of the proposed reverse design methodology.
基金supported by the National Natural Science Foundation of China under Grant 62301051.
文摘Range-azimuth imaging of ground targets via frequency-modulated continuous wave(FMCW)radar is crucial for effective target detection.However,when the pitch of the moving array constructed during motion exceeds the physical array aperture,azimuth ambiguity occurs,making range-azimuth imaging on a moving platform challenging.To address this issue,we theoretically analyze azimuth ambiguity generation in sparse motion arrays and propose a dual-aperture adaptive processing(DAAP)method for suppressing azimuth ambiguity.This method combines spatial multiple-input multiple-output(MIMO)arrays with sparse motion arrays to achieve high-resolution range-azimuth imaging.In addition,an adaptive QR decomposition denoising method for sparse array signals based on iterative low-rank matrix approximation(LRMA)and regularized QR is proposed to preprocess sparse motion array signals.Simulations and experiments show that on a two-transmitter-four-receiver array,the signal-to-noise ratio(SNR)of the sparse motion array signal after noise suppression via adaptive QR decomposition can exceed 0 dB,and the azimuth ambiguity signal ratio(AASR)can be reduced to below-20 dB.
基金supported by the National Key R&D Program of China(Grant No.2023YFC3010803)the National Nature Science Foundation of China(Grant No.52272424)+1 种基金the Key R&D Program of Hubei Province of China(Grant No.2023BCB123)the Fundamental Research Funds for the Central Universities(Grant No.WUT:2023IVB079)。
文摘Side-scan sonar(SSS)is now a prevalent instrument for large-scale seafloor topography measurements,deployable on an autonomous underwater vehicle(AUV)to execute fully automated underwater acoustic scanning imaging along a predetermined trajectory.However,SSS images often suffer from speckle noise caused by mutual interference between echoes,and limited AUV computational resources further hinder noise suppression.Existing approaches for SSS image processing and speckle noise reduction rely heavily on complex network structures and fail to combine the benefits of deep learning and domain knowledge.To address the problem,Rep DNet,a novel and effective despeckling convolutional neural network is proposed.Rep DNet introduces two re-parameterized blocks:the Pixel Smoothing Block(PSB)and Edge Enhancement Block(EEB),preserving edge information while attenuating speckle noise.During training,PSB and EEB manifest as double-layered multi-branch structures,integrating first-order and secondorder derivatives and smoothing functions.During inference,the branches are re-parameterized into a 3×3 convolution,enabling efficient inference without sacrificing accuracy.Rep DNet comprises three computational operations:3×3 convolution,element-wise summation and Rectified Linear Unit activation.Evaluations on benchmark datasets,a real SSS dataset and Data collected at Lake Mulan aestablish Rep DNet as a well-balanced network,meeting the AUV computational constraints in terms of performance and latency.
文摘Objective To observe the cervical elasticity of healthy adult nulliparous women at different age groups and different stages of menstrual cycle with E-Cervix imaging technology.Methods A total of 218 healthy adult nulliparous women who underwent transvaginal ultrasound examination for routine physical examination were retrospectively enrolled,including 103 in follicular phase,78 in ovulation phase and 37 in luteal phase.Cervical canal length(CL)and E-Cervix elasticity parameters were compared among different age groups and different stages of menstrual cycle,including elasticity contrast index(ECI),hardness ratio(HR),cervical internal and external orifice strain values(IOS and EOS)and IOS/EOS ratio.Results No significant difference of CL nor cervical elasticity parameters was detected among healthy adult nulliparous women at different age groups(all P>0.05).There were significant differences of ECI,HR and IOS among different menstrual cycle stages(all P<0.05),among which women in follicular phase had higher ECI and IOS but lower HR than those in luteal phase(all P<0.05).Conclusion No significant difference of cervical elasticity existed among healthy adult nulliparous women at different age groups.Meanwhile,cervical elasticity of healthy adult nulliparous women changed during menstrual cycle,in follicular phase had higher ECI and IOS but lower HR than in luteal phase.
基金Supported by the Zhejiang Provincial"Jianbing"and"Lingyan"R&D Programs(2023C03012,2024C01126)。
文摘The encoding aperture snapshot spectral imaging system,based on the compressive sensing theory,can be regarded as an encoder,which can efficiently obtain compressed two-dimensional spectral data and then decode it into three-dimensional spectral data through deep neural networks.However,training the deep neural net⁃works requires a large amount of clean data that is difficult to obtain.To address the problem of insufficient training data for deep neural networks,a self-supervised hyperspectral denoising neural network based on neighbor⁃hood sampling is proposed.This network is integrated into a deep plug-and-play framework to achieve self-supervised spectral reconstruction.The study also examines the impact of different noise degradation models on the fi⁃nal reconstruction quality.Experimental results demonstrate that the self-supervised learning method enhances the average peak signal-to-noise ratio by 1.18 dB and improves the structural similarity by 0.009 compared with the supervised learning method.Additionally,it achieves better visual reconstruction results.
基金Supported by the National Natural Science Foundation of China(42221002,42171432)Shanghai Municipal Science and Technology Major Project(2021SHZDZX0100)the Fundamental Research Funds for the Central Universities.
文摘The geometric accuracy of topographic mapping with high-resolution remote sensing images is inevita-bly affected by the orbiter attitude jitter.Therefore,it is necessary to conduct preliminary research on the stereo mapping camera equipped on lunar orbiter before launching.In this work,an imaging simulation method consid-ering the attitude jitter is presented.The impact analysis of different attitude jitter on terrain undulation is conduct-ed by simulating jitter at three attitude angles,respectively.The proposed simulation method is based on the rigor-ous sensor model,using the lunar digital elevation model(DEM)and orthoimage as reference data.The orbit and attitude of the lunar stereo mapping camera are simulated while considering the attitude jitter.Two-dimensional simulated stereo images are generated according to the position and attitude of the orbiter in a given orbit.Experi-mental analyses were conducted by the DEM with the simulated stereo image.The simulation imaging results demonstrate that the proposed method can ensure imaging efficiency without losing the accuracy of topographic mapping.The effect of attitude jitter on the stereo mapping accuracy of the simulated images was analyzed through a DEM comparison.
基金Science,Technology and Innovation Project of Xiongan New Area (Grant No.2022XAGG0181)LiaoNing Revitalization Talents Program (Grant No.XLYC2007074)+1 种基金Shenyang Young and Middle-aged Science and Technology Innovation Talent Support Program (Grant No.RC220523)Natural Science Foundation of Liaoning Province of China (Grant Nos.2022-YGJC-03 and 2022-MS-034)to provide fund for conducting experiments。
文摘This paper investigates a new vortex wave imaging approach to improve the imaging quality of small metal targets of size less than 1.5 mm.Antennas with different spiral phase plates are designed to efficiently transmit vortex beams with orbital angular momentums(OAMs).By analyzing the OAM spectrum of the target,it was discovered that the predominant reflection contains a particular OAM mode that carries abundant azimuthal information.This can be explained by the OAM selectivity of the target and the guidance of the vortex transmitting beam.A simple reflection vortex imaging system was designed to capture the phase information.Measurement results show that the high image contrast reaches 14.9%,which is twice as high as that of the imaging without OAM.Both of simulations and experiments demonstrate that the vortex phase imaging approach proposed in this paper can effectively improve the imaging quality at 80 GHz.This approach is suitable for other millimeter wave imaging systems and is helpful to improve the resolution in anti-terrorism security checks.
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
文摘In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantly degrades image quality.Traditional denoising methods,typically based on filter techniques,often face challenges related to inefficiency and limited adaptability.To address these limitations,this study proposes a novel SAR image denoising algorithm based on an enhanced residual network architecture,with the objective of enhancing the utility of SAR imagery in complex electromagnetic environments.The proposed algorithm integrates residual network modules,which directly process the noisy input images to generate denoised outputs.This approach not only reduces computational complexity but also mitigates the difficulties associated with model training.By combining the Transformer module with the residual block,the algorithm enhances the network's ability to extract global features,offering superior feature extraction capabilities compared to CNN-based residual modules.Additionally,the algorithm employs the adaptive activation function Meta-ACON,which dynamically adjusts the activation patterns of neurons,thereby improving the network's feature extraction efficiency.The effectiveness of the proposed denoising method is empirically validated using real SAR images from the RSOD dataset.The proposed algorithm exhibits remarkable performance in terms of EPI,SSIM,and ENL,while achieving a substantial enhancement in PSNR when compared to traditional and deep learning-based algorithms.The PSNR performance is enhanced by over twofold.Moreover,the evaluation of the MSTAR SAR dataset substantiates the algorithm's robustness and applicability in SAR denoising tasks,with a PSNR of 25.2021 being attained.These findings underscore the efficacy of the proposed algorithm in mitigating speckle noise while preserving critical features in SAR imagery,thereby enhancing its quality and usability in practical scenarios.
文摘Image super-resolution reconstruction technology is currently widely used in medical imaging,video surveillance,and industrial quality inspection.It not only enhances image quality but also improves details and visual perception,significantly increasing the utility of low-resolution images.In this study,an improved image superresolution reconstruction model based on Generative Adversarial Networks(SRGAN)was proposed.This model introduced a channel and spatial attention mechanism(CSAB)in the generator,allowing it to effectively leverage the information from the input image to enhance feature representations and capture important details.The discriminator was designed with an improved PatchGAN architecture,which more accurately captured local details and texture information of the image.With these enhanced generator and discriminator architectures and an optimized loss function design,this method demonstrated superior performance in image quality assessment metrics.Experimental results showed that this model outperforms traditional methods,presenting more detailed and realistic image details in the visual effects.
文摘Low-light image enhancement is one of the most active research areas in the field of computer vision in recent years.In the low-light image enhancement process,loss of image details and increase in noise occur inevitably,influencing the quality of enhanced images.To alleviate this problem,a low-light image enhancement model called RetinexNet model based on Retinex theory was proposed in this study.The model was composed of an image decomposition module and a brightness enhancement module.In the decomposition module,a convolutional block attention module(CBAM)was incorporated to enhance feature representation capacity of the network,focusing on crucial features and suppressing irrelevant ones.A multifeature fusion denoising module was designed within the brightness enhancement module,circumventing the issue of feature loss during downsampling.The proposed model outperforms the existing algorithms in terms of PSNR and SSIM metrics on the publicly available datasets LOL and MIT-Adobe FiveK,as well as gives superior results in terms of NIQE metrics on the publicly available dataset LIME.
文摘In recent years,with the development of synthetic aperture radar(SAR)technology and the widespread application of deep learning,lightweight detection of SAR images has emerged as a research direction.The ultimate goal is to reduce computational and storage requirements while ensuring detection accuracy and reliability,making it an ideal choice for achieving rapid response and efficient processing.In this regard,a lightweight SAR ship target detection algorithm based on YOLOv8 was proposed in this study.Firstly,the C2f-Sc module was designed by fusing the C2f in the backbone network with the ScConv to reduce spatial redundancy and channel redundancy between features in convolutional neural networks.At the same time,the Ghost module was introduced into the neck network to effectively reduce model parameters and computational complexity.A relatively lightweight EMA attention mechanism was added to the neck network to promote the effective fusion of features at different levels.Experimental results showed that the Parameters and GFLOPs of the improved model are reduced by 8.5%and 7.0%when mAP@0.5 and mAP@0.5:0.95 are increased by 0.7%and 1.8%,respectively.It makes the model lightweight and improves the detection accuracy,which has certain application value.
