Prostate cancer(PCa)is characterized by high incidence and propensity for easy metastasis,presenting significant challenges in clinical diagnosis and treatment.Tumor microenvironment(TME)-responsive nanomaterials prov...Prostate cancer(PCa)is characterized by high incidence and propensity for easy metastasis,presenting significant challenges in clinical diagnosis and treatment.Tumor microenvironment(TME)-responsive nanomaterials provide a promising prospect for imaging-guided precision therapy.Considering that tumor-derived alkaline phosphatase(ALP)is over-expressed in metastatic PCa,it makes a great chance to develop a theranostics system with ALP responsive in the TME.Herein,an ALP-responsive aggregationinduced emission luminogens(AIEgens)nanoprobe AMNF self-assembly was designed for enhancing the diagnosis and treatment of metastatic PCa.The nanoprobe exhibited self-aggregation in the presence of ALP resulted in aggregation-induced fluorescence,and enhanced accumulation and prolonged retention period at the tumor site.In terms of detection,the fluorescence(FL)/computed tomography(CT)/magnetic resonance(MR)multi-mode imaging effect of nanoprobe was significantly improved post-aggregation,enabling precise diagnosis through the amalgamation of multiple imaging modes.Enhanced CT/MR imaging can achieve assist preoperative tumor diagnosis,and enhanced FL imaging technology can achieve“intraoperative visual navigation”,showing its potential application value in clinical tumor detection and surgical guidance.In terms of treatment,AMNF showed strong absorption in the near infrared region after aggregation,which improved the photothermal treatment effect.Overall,our work developed an effective aggregation-enhanced theranostic strategy for ALP-related cancers.展开更多
Background:Medical imaging advancements are constrained by fundamental trade-offs between acquisition speed,radiation dose,and image quality,forcing clinicians to work with noisy,incomplete data.Existing reconstructio...Background:Medical imaging advancements are constrained by fundamental trade-offs between acquisition speed,radiation dose,and image quality,forcing clinicians to work with noisy,incomplete data.Existing reconstruction methods either compromise on accuracy with iterative algorithms or suffer from limited generalizability with task-specific deep learning approaches.Methods:We present LDM-PIR,a lightweight physics-conditioned diffusion multi-model for medical image reconstruction that addresses key challenges in magnetic resonance imaging(MRI),CT,and low-photon imaging.Unlike traditional iterative methods,which are computationally expensive,or task-specific deep learning approaches lacking generalizability,integrates three innovations.A physics-conditioned diffusion framework that embeds acquisition operators(Fourier/Radon transforms)and noise models directly into the reconstruction process.A multi-model architecture that unifies denoising,inpainting,and super-resolution via shared weight conditioning.A lightweight design(2.1M parameters)enabling rapid inference(0.8s/image on GPU).Through self-supervised fine-tuning with measurement consistency losses adapts to new imaging modalities using fewer annotated samples.Results:Achieves state-of-the-art performance on fastMRI(peak signal-to-noise ratio(PSNR):34.04 for single-coil/31.50 for multi-coil)and Lung Image Database Consortium and Image Database Resource Initiative(28.83 PSNR under Poisson noise).Clinical evaluations demonstrate superior preservation of anatomical structures,with SSIM improvements of 8.8%for single-coil and 4.36%for multi-coil MRI over uDPIR.Conclusion:It offers a flexible,efficient,and scalable solution for medical image reconstruction,addressing the challenges of noise,undersampling,and modality generalization.The model’s lightweight design allows for rapid inference,while its self-supervised fine-tuning capability minimizes reliance on large annotated datasets,making it suitable for real-world clinical applications.展开更多
Raman imaging,as a molecular spectroscopy technique,has been widely studied and applied in research fields such as life sciences and food safety due to its excellent specificity and high resolution.However,its develop...Raman imaging,as a molecular spectroscopy technique,has been widely studied and applied in research fields such as life sciences and food safety due to its excellent specificity and high resolution.However,its development still faces challenges such as weak signals,slow acquisition speed,and insufficient penetration depth.In recent years,the rapid development of aggregate science has provided new insights for addressing these limitations.Aggregation-induced emission(AIE)materials exhibit enhanced signals in the aggregated state,which may compensate for the inherent weak Raman signals.This article reviews the cutting-edge progress of Raman imaging technology and its current status in cross-disciplinary research with aggregate science,emphasizing the strategy of constructing AIE-Raman dual-responsive probes through molecular engineering to achieve functional complementarity between fluorescence localization and Raman quantification,thereby significantly improving detection sensitivity and specificity.These probes have demonstrated single-cell resolution and high spatiotemporal accuracy in applications such as tumor surgical navigation,diagnosis and treatment of drug-resistant bacteria,and dynamic monitoring of organelles.We also analyze the bottlenecks in this field,such as biological safety and the complexity of molecular design,and outline the future development directions,including intelligent responsive probes,artificial intelligence-assisted analysis,and multimodal fusion platforms.The integration of Raman imaging and AIE sheds new light in the field of medical imaging.展开更多
Metasurfaces are artificial structures that can finely control the characteristics of electromagnetic waves at subwavelength scales,and they are widely used to manipulate the propagation,phase,amplitude,and polariza⁃t...Metasurfaces are artificial structures that can finely control the characteristics of electromagnetic waves at subwavelength scales,and they are widely used to manipulate the propagation,phase,amplitude,and polariza⁃tion of light.In this work,a bound state in the continuum(BIC)structure based on a metallic metasurface is pro⁃posed.By adjusting the metallic structure using CST and COMSOL software,a significant quasi-BIC peak can be achieved at a frequency of 0.8217 terahertz(THz).Through multi-level expansion analysis,it is found that the electric dipole(ED)is the main factor contributing to the resonant characteristics of the structure.By leveraging the characteristics of BIC,an imaging system was created and operated.According to the simulation results,the imaging system demonstrated excellent sensitivity and resolution,revealing the great potential of terahertz imag⁃ing.This research not only provides new ideas for the creation of BIC structures but also offers an effective refer⁃ence for the development of high-performance terahertz imaging technology.展开更多
Two novel aggregation-induced emission(AIE)-active probes,TPA-H and TPA-2 F,were designed and synthesized based on a triphenylamine(TPA)core.Systematic characterization demonstrated that both probes exhibit excellent ...Two novel aggregation-induced emission(AIE)-active probes,TPA-H and TPA-2 F,were designed and synthesized based on a triphenylamine(TPA)core.Systematic characterization demonstrated that both probes exhibit excellent biocompatibility(cell viability>90%at concentrations up to 50μmol/L)and outstanding LD-targeting speci⁃ficity with minimal colocalization with other organelles such as mitochondria and lysosomes.During early differentia⁃tion of 3 T 3-L 1 adipocytes,both TPA-2 F and TPA-H clearly visualized small and nascent LDs that were difficult to be detected with BODIPY,indicating superior imaging sensitivity compared to the existing fluorescent probes for LDs.Moreover,TPA-2 F demonstrated exceptional photostability,retaining over 90%of its initial fluorescence intensity after 100 continuous laser scanning cycles,significantly outperforming TPA-H.This work not only provides two high-performance LD imaging tools but also highlights the potential of AIE luminogens(AIEgens)in organelle-specific bioimaging,offering promising avenues for early diagnosis and mechanistic research of lipid-related metabolic diseases.展开更多
Neuromorphic cameras,or dynamic vision sensors,are bio-inspired event cameras that measure changes in the image brightness asynchronously and independently at the pixel level.Recently,they garnered increasing interest...Neuromorphic cameras,or dynamic vision sensors,are bio-inspired event cameras that measure changes in the image brightness asynchronously and independently at the pixel level.Recently,they garnered increasing interest due to their extremely high temporal resolution,wide dynamic range,low power consumption,and high pixel bandwidth.Despite their advantages,most existing three-dimensional (3D) event imaging solutions rely on multicamera configurations,which are costly,complex,and challenging to synchronize.In this study,we introduce a new framework for four-dimensional (4D) event imaging using a single static neuromorphic camera.We take advantage of the inherent sparsity of event data to combine optically encoded stereo channels into a single event camera.By utilizing optical channel multiplexing,we maintain sensor resolution while retaining the key advantages of event cameras.展开更多
Metal organic framework(MOF) assembled with coordination bonds has the disadvantage of poor stability that limits its application in the field of stationary phase,while covalent organic framework(COF)assembled through...Metal organic framework(MOF) assembled with coordination bonds has the disadvantage of poor stability that limits its application in the field of stationary phase,while covalent organic framework(COF)assembled through covalent bonds exhibits excellent structural stability.It has been shown that the stationary phases prepared by combining MOF and COF can make up for the poor stability of MOF@SiO_(2),and the MOF/COF composites have superior chromatographic separation performance.However,the traditional methods for preparing COF/MOF based stationary phases are generally solvent thermal synthesis.In this study,a green and low-cost synthesis method was proposed for the preparation of MOF/COF@SiO_(2) stationary phase.Firstly,COF@SiO_(2) was prepared in a choline chloride/ethylene glycol based deep eutectic solvent(DES).Secondly,another acid-base tunable DES prepared by mixing p-toluenesulfonic acid(PTSA)and 2-methylimidazole in different proportions was introduced as the reaction solvent and reactant for rapid synthesis of MOF/COF@SiO_(2).Compared with the toxic transition metal-based MOFs selected in most previous studies,a lightweight and non-toxic S-zone metal(calcium) based MOF was employed in this study.PTSA and calcium will form the calcium/oxygen-containing organic acid framework in acidic DES,which assembles with terephthalic acid dissolved in basic DES to form MOF.The strong hydrogen bonding effect of DES can facilitate rapid assembly of Ca-MOF.The obtained Ca-MOF/COF@SiO_(2) can be used for multi-mode chromatography to efficiently separate multiple isomeric/hydrophilic/hydrophobic analytes.The synthesis method of Ca-MOF/COF@SiO_(2) is green and mild,especially the use of acid-base tunable DES promotes the rapid synthesis of non-toxic Ca-MOF/COF@silica composites,which offers an innovative approach of greenly synthesizing novel MOF/COF stationary phases and extends their applications in the field of chromatography.展开更多
Background:Sarcomatoid carcinoma of the ureter(SCU)is a highly aggressive and relatively uncommon malignant tumor of the urinary tract.Its frequency is quite low,and its prognosis is very bad when compared to other ca...Background:Sarcomatoid carcinoma of the ureter(SCU)is a highly aggressive and relatively uncommon malignant tumor of the urinary tract.Its frequency is quite low,and its prognosis is very bad when compared to other cancers of the urinary system.SCU clinical reports are still hard to come by.MRI and PEI/CT imaging of ureteral sarcomatoid cancer is presented in this case to promote diagnostic awareness and comprehension of the imaging characteristics of this uncommon illness.Method:The patient had ureteral sarcomatoid cancer,which was verified by pathological investigation after ureteroscopic biopsy.The patient’s clinical information,imaging results,surgical outcomes,and pathological findings were gathered.A retrospective study was carried out in combinationwith pertinent national and international literature.Results:An 84-year-old female patient was admitted for“left flank discomfort lasting over one month.”MRI revealed an irregular soft tissue mass in the middle-lower segment of the left ureter.T2-weighted imaging showed an unevenly slightly hyperintense signal.Diffusion-weighted imaging demonstrated restricted diffusion.Contrastenhanced imaging exhibited heterogeneous enhancement.PET/CT demonstrated significantly increased fluorodeoxyglucose metabolism in the mass with secondary left upper urinary tract obstruction.Concurrent findings included a solitary metastatic lesion in hepatic segment S6 and multiple lymph node metastases along the left common iliac and external iliac arteries.Preoperative diagnosis suggested a malignant tumor of the ureter.The patient underwent left nephroureteroscopy with biopsy,and the postoperative pathological diagnosis was ureteral sarcomatoid carcinoma.Conclusion:Ureteral sarcomatoid carcinoma is a rare,highly malignant,and aggressive tumor with nonspecific imaging features,typically presenting as an invasively growing mass.Diagnosis relies on postoperative pathology and immunohistochemical examination.MRI and PET/CT scans are valuable for preoperative localization and characterization,tumor staging,treatment planning,and postoperative follow-up.The prognosis is extremely negative.The main treatment option is radical surgery,although constant monitoring is necessary since early recurrence and metastases are frequent after surgery.展开更多
The level of glutathione(GSH)is significantly associated with numerous pathological processes,thus,real-time detection of the GSH level is of significance for early diagnosis of GSH-related diseases.Herein,we develope...The level of glutathione(GSH)is significantly associated with numerous pathological processes,thus,real-time detection of the GSH level is of significance for early diagnosis of GSH-related diseases.Herein,we developed in vivo second near-infrared(NIR-II)window fluorescence(FL)and ratiometric photoacoustic(RPA)dual-modality imaging of GSH using a GSH-activatable probe(LET-14).LET-14 was synthesized based on a rhodamine hybrid xanthene skeleton with a FL shielding 2,4-dinitrobenzene sulfonyl group that can be specifically cleaved by GSH,thus resulting in a markedly bathochromic-shift absorption,a 6.5-fold increase in NIR-II FL intensity(FL_(920))and a 13-fold increase in RPA signal(PA_(880)/PA_(705))in vitro.Intriguingly,LET-14 exhibits good selectivity and sensitivity for NIR-II FL and RPA dual-modality imaging of GSH in 4T1 tumor-bearing mouse model.Our findings develop an in vivo detection tool of GSH,which has great potential in the field of cancer diagnosis.展开更多
The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-effic...The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.展开更多
Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their dia...Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their diagnostic reliability.This review presents a structured and comprehensive analysis of advanced histogram equalization(HE)-based techniques for medical image enhancement.Our review methodology encompasses:(1)classical HE approaches and related limitations in medical domains;(2)adaptive schemes like Adaptive Histogram Equalization(AHE)and Contrast Limited Adaptive Histogrma Equalization(CLAHE)and their advance variants;(3)brightnesspreserving schemes like BBHE and MMBEBHE and related algorithms;(4)dynamic and recursive histogram equalization methods incorporating DHE and RMSHE;(5)fuzzy logic-based enhancement methodologies addressing uncertainty and noise in medical images;and(6)hybrid optimization methodologies through the application of metaheuristic algorithms(World Cup Optimization,Particle Swarm Optimization,Genetic Algorithms,along with histogram-based methodologies.)There is also a comparative discussion given based on contrast improvement,image brightness preservation,noise management,and computational efficiency.Such advancements have better capabilities of improving image quality,which is more important for improved diagnosis and image analysis.展开更多
Electrons in the energy range of 10–100 keV are important energetic particle components in the magnetosphere,and they play a key role in many physical processes in the magnetosphere.However,many scientific questions ...Electrons in the energy range of 10–100 keV are important energetic particle components in the magnetosphere,and they play a key role in many physical processes in the magnetosphere.However,many scientific questions about these processes are still unanswered.High spatiotemporal and energy-resolution imaging detection of 10–100 keV electrons is of great significance for solving these scientific problems.The traditional space particle detection technology cannot effectively detect the medium-energy electrons in this energy range.In this project,we propose combining low-noise particle detection technology with pinhole imaging technology to achieve high-resolution imaging detection of 10–100 keV medium-energy electrons in the magnetosphere,and at the same time achieve miniaturization(≤3.2 kg and size of 150×150×170 mm)and low power consumption(≤5 W)of the instrument,which can be used for space physics research and space weather applications in the future.展开更多
The unique advantage of x-ray ghost imaging(XGI)is its potential in low dose radiology.One of the practical ways to reduce the radiation exposure is to reduce the measurements while remaining sufficient image quality....The unique advantage of x-ray ghost imaging(XGI)is its potential in low dose radiology.One of the practical ways to reduce the radiation exposure is to reduce the measurements while remaining sufficient image quality.Synthetic aperture x-ray ghost imaging(SAXGI)is invented to achieve megapixel XGI with limited measurements,which is expected to implement XGI simultaneously with large field of view and low radiation exposure.In this paper,we experimentally investigate the effect of measurements reduction on the spatial resolution and image quality of SAXGI with standard sample and biomedical specimen.The results with a resolution chart demonstrated that at 360 measurements,SAXGI successfully retrieved the sample image of 1960×1960 pixels with spatial resolution of 4μm.With measurement reduction,the spatial resolution deteriorates but the sparser structures are still discernable.Even with measurements reduced to 10,a spatial resolution of 10μm can still be achieved by SAXGI.A biomedical sample of a fish specimen is employed to evaluate the method and the fish image of 2000×1000 pixels with an SSIM of 0.962 is reconstructed by SAXGI with 770measurements,corresponding to an accumulative exposure reduction of more than 2 times.With the measurements reduced to 10 which corresponds to 1/160 of the accumulative radiation exposure for conventional radiology,bulky structure like the fish skeleton can still be definitely discerned and the SSIM for the reconstructed image still retained 0.9179.Results of this paper demonstrate that measurements reduction is practicable for the radiation exposure reduction of the sample,which implicates that SAXGI with limited measurements is an efficient solution for low dose radiology.展开更多
The flow behavior of molten steel in the thin slab mold under high casting speed conditions was investigated,with a focus on the multi-mode continuous casting and rolling mold.A steel-slag two-phase flow model was est...The flow behavior of molten steel in the thin slab mold under high casting speed conditions was investigated,with a focus on the multi-mode continuous casting and rolling mold.A steel-slag two-phase flow model was established using large eddy simulation,the volume of fluid,and magnetohydrodynamics methods through numerical simulation.The maximum flow velocity and wave height at the steel-slag interface within the mold are critical evaluation criteria for analyzing asymmetric flow under varying casting speeds and electromagnetic braking.The results indicate that the asymmetric flows within the mold do not occur synchronously.The severity of the asymmetric flow correlates with the velocity difference across the steel-slag interface.A greater biased flow prolongs the time required to revert to a steady state.When the magnetic field intensity is set to 0.24 T and the magnetic pole position is at 390 mm from the steel-slag interface,this configuration can reduce the velocity of the steel-slag interface,thereby mitigating the asymmetric flow.Additionally,it can diminish the velocity,impact depth,and impact intensity on the narrow face of the jet,thus improving the distribution of velocity and turbulent kinetic energy within the mold.This configuration prolongs the time required for the steel-slag interface to transition from a stable state to its maximum velocity and shortens the time for the interface to return to stability from an unstable state.Moreover,it ensures the positional stability of the steel-slag interface,confining its position within−3 mm.展开更多
Generative Adversarial Networks(GANs)have become valuable tools in medical imaging,enabling realistic image synthesis for enhancement,augmentation,and restoration.However,their integration into clinical workflows rais...Generative Adversarial Networks(GANs)have become valuable tools in medical imaging,enabling realistic image synthesis for enhancement,augmentation,and restoration.However,their integration into clinical workflows raises concerns,particularly the risk of subtle distortions or hallucinations that may undermine diagnostic accuracy and weaken trust in AI-assisted decision-making.To address this challenge,we propose a hybrid deep learning framework designed to detect GAN-induced artifacts in medical images,thereby reinforcing the reliability of AI-driven diagnostics.The framework integrates low-level statistical descriptors,including high-frequency residuals and Gray-Level Co-occurrence Matrix(GLCM)texture features,with high-level semantic representations extracted from a pre-trained ResNet18.This dual-stream approach enables detection of both pixel-level anomalies and structural inconsistencies introduced by GAN-based manipulation.We validated the framework on a curated dataset of 10,000 medical images,evenly split between authentic and GAN-generated samples across four modalities:MRI,CT,X-ray,and fundus photography.To improve generalizability to real-world clinical settings,we incorporated domain adaptation strategies such as adversarial training and style transfer,reducing domain shift by 15%.Experimental results demonstrate robust performance,achieving 92.6%accuracy and an F1-score of 0.91 on synthetic test data,and maintaining strong performance on real-world GAN-modified images with 87.3%accuracy and an F1-score of 0.85.Additionally,the model attained an AUC of 0.96 and an average precision of 0.92,outperforming conventional GAN detection pipelines and baseline Convolutional Neural Network(CNN)architectures.These findings establish the proposed framework as an effective and reliable solution for detecting GAN-induced hallucinations in medical imaging,representing an important step toward building trustworthy and clinically deployable AI systems.展开更多
Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accel...Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accelerator systems.This breakthrough opens up new possibilities for laboratory-scale light sources.All-optical inverse Compton scattering(AOCS)sources driven by LWFAs produce high-brightness,quasimonochromatic X rays with micrometer-scale source sizes,delivering the spatial coherence and resolution required for X-ray phase-contrast imaging(XPCI).These features position AOCS X-ray sources as promising tools for applications in biology,medicine,physics,and materials science.However,previous AOCS-based imaging studies have primarily focused on X-ray absorption imaging.In this work,we report successful experimental demonstrations of edge-enhanced in-line XPCI using energy-tunable,quasi-monochromatic AOCS X rays.With a spatial resolution of~20μm,our results clearly show the potential of high-resolution,AOCS-based XPCI applications.展开更多
Brain tumours disrupt the normal functioning of the brain and,if left untreated,can invade surrounding tissues,blood vessels,and nerves,posing a severe threat.Consequently,early detection is crucial to prevent tragic ...Brain tumours disrupt the normal functioning of the brain and,if left untreated,can invade surrounding tissues,blood vessels,and nerves,posing a severe threat.Consequently,early detection is crucial to prevent tragic outcomes.Distinguishing brain tumours through manual detection poses a significant challenge given their diverse features,such as differing shapes,sizes,and nucleus characteristics.Therefore,this research introduces an improved architecture for tumour detection named as Brain-RetinaNet,an extension of the RetinaNet model.Brain-RetinaNet is specifically designed for automated detection and identification of brain tumours in MRI images.It utilises an advanced multiscale feature fusion mechanism within the X-module,complemented by the channel attention module.The feature fusion mechanism within the X-module progressively merges features from different scales,producing enriched feature maps that encompass valuable information.At the same time,the attention module dynamically allocates optimal weights to individual channels within the feature map,enabling the network to prioritise relevant features while reducing interference from unnecessary ones.Moreover,this study employs data augmentation technique to address the limitation of a limited number of available samples.Experimental results indicate that Brain-RetinaNet outperforms existing detectors such as YOLO,SSD,Centernet,EfficientNet,and M2det for the brain tumour detection from MRI images.展开更多
In recent years,the rapid advancement of artificial intelligence(AI)technology has enabled AI-assisted negative screening to significantly enhance physicians'efficiency through image feature analysis and multimoda...In recent years,the rapid advancement of artificial intelligence(AI)technology has enabled AI-assisted negative screening to significantly enhance physicians'efficiency through image feature analysis and multimodal data modeling,allowing them to focus more on diagnosing positive cases.Meanwhile,multispectral imaging(MSI)integrates spectral and spatial resolution to capture subtle tissue features invisible to the human eye,providing high-resolution data support for pathological analysis.Combining AI technology with MSI and employing quantitative methods to analyze multiband biomarkers(such as absorbance differences in keratin pearls)can effectively improve diagnostic specificity and reduce subjective errors in manual slide interpretation.To address the challenge of identifying negative tissue sections,we developed a discrimination algorithm powered by MSI.We demonstrated its efficacy using cutaneous squamous cell carcinoma(cSCC)as a representative case study.The algorithm achieved 100%accuracy in excluding negative cases and effectively mitigated the false-positive problem caused by cSCC heterogeneity.We constructed a multispectral image(MSI)dataset acquired at 520 nm,600 nm,and 630 nm wavelengths.Subsequently,we employed an optimized MobileViT model for tissue classification and performed comparative analyses against other models.The experimental results showed that our optimized MobileViT model achieved superior performance in identifying negative tissue sections,with a perfect accuracy rate of 100%.Thus,our results confirm the feasibility of integrating MSI with AI to exclude negative cases with perfect accuracy,offering a novel solution to alleviate the workload of pathologists.展开更多
Optical imaging has been pivotal in biological research(e.g.,cellular/developmental biology)for over two centuries.Recent advances like super-resolution fluorescence and nonlinear optical microscopy enable nanoscale s...Optical imaging has been pivotal in biological research(e.g.,cellular/developmental biology)for over two centuries.Recent advances like super-resolution fluorescence and nonlinear optical microscopy enable nanoscale studies of live cells and animals,yet their application to marine mollusks-key marine ecosystem species,remains underexplored.This review summarizes optical imaging techniques and their use in investigating marine mollusks across molecular,cellular,tissue,and individual levels.It highlights promising avenues for novel imaging methods to unravel the structures and functions of these organisms in future research,with a focus on advancements in applying cutting-edge optical techniques across these hierarchical levels.Given optical imaging's significance in elucidating marine mollusks'ecological and genetic information,this field deserves substantial attention and support.The review aims to address existing gaps,providing researchers and practitioners with comprehensive insights to foster further progress in this domain.展开更多
In complex media scattering,multiple scattering severely degrades the optical wavefront and results in blurred images,while the spectral distortion caused by the scattering effect leads to severe color distortion.Achi...In complex media scattering,multiple scattering severely degrades the optical wavefront and results in blurred images,while the spectral distortion caused by the scattering effect leads to severe color distortion.Achieving color high-resolution imaging through scattering media remains a significant challenge.Here,we propose a broadband,polarization-based method for color high-resolution imaging through scattering media.This approach enables high-resolution reconstruction by effectively separating the speckle illumination pattern from the mixed-scattering field information,leveraging polarization common-mode characteristics.Concurrently,it incorporates chromatic balance compensation to correct spectral aliasing in the scattered light field,enabling color high-resolution imaging through complex scattering media.To further optimize color distortion caused by scattering,a compensation strategy combining color constancy and white balance theory is adopted.Experimental results demonstrate that the proposed method significantly enhances both spatial resolution and color fidelity across various scattering conditions and target materials,showcasing strong adaptability and robustness.This approach provides an effective solution for achieving high-resolution color optical imaging in complex scattering environments.展开更多
基金supported by Natural Science Foundation of Jilin Province(No.SKL202302002)Key Research and Development project of Jilin Provincial Science and Technology Department(No.20210204142YY)+2 种基金The Science and Technology Development Program of Jilin Province(No.2020122256JC)Beijing Kechuang Medical Development Foundation Fund of China(No.KC2023-JX-0186BQ079)Talent Reserve Program(TRP),the First Hospital of Jilin University(No.JDYY-TRP-2024007)。
文摘Prostate cancer(PCa)is characterized by high incidence and propensity for easy metastasis,presenting significant challenges in clinical diagnosis and treatment.Tumor microenvironment(TME)-responsive nanomaterials provide a promising prospect for imaging-guided precision therapy.Considering that tumor-derived alkaline phosphatase(ALP)is over-expressed in metastatic PCa,it makes a great chance to develop a theranostics system with ALP responsive in the TME.Herein,an ALP-responsive aggregationinduced emission luminogens(AIEgens)nanoprobe AMNF self-assembly was designed for enhancing the diagnosis and treatment of metastatic PCa.The nanoprobe exhibited self-aggregation in the presence of ALP resulted in aggregation-induced fluorescence,and enhanced accumulation and prolonged retention period at the tumor site.In terms of detection,the fluorescence(FL)/computed tomography(CT)/magnetic resonance(MR)multi-mode imaging effect of nanoprobe was significantly improved post-aggregation,enabling precise diagnosis through the amalgamation of multiple imaging modes.Enhanced CT/MR imaging can achieve assist preoperative tumor diagnosis,and enhanced FL imaging technology can achieve“intraoperative visual navigation”,showing its potential application value in clinical tumor detection and surgical guidance.In terms of treatment,AMNF showed strong absorption in the near infrared region after aggregation,which improved the photothermal treatment effect.Overall,our work developed an effective aggregation-enhanced theranostic strategy for ALP-related cancers.
文摘Background:Medical imaging advancements are constrained by fundamental trade-offs between acquisition speed,radiation dose,and image quality,forcing clinicians to work with noisy,incomplete data.Existing reconstruction methods either compromise on accuracy with iterative algorithms or suffer from limited generalizability with task-specific deep learning approaches.Methods:We present LDM-PIR,a lightweight physics-conditioned diffusion multi-model for medical image reconstruction that addresses key challenges in magnetic resonance imaging(MRI),CT,and low-photon imaging.Unlike traditional iterative methods,which are computationally expensive,or task-specific deep learning approaches lacking generalizability,integrates three innovations.A physics-conditioned diffusion framework that embeds acquisition operators(Fourier/Radon transforms)and noise models directly into the reconstruction process.A multi-model architecture that unifies denoising,inpainting,and super-resolution via shared weight conditioning.A lightweight design(2.1M parameters)enabling rapid inference(0.8s/image on GPU).Through self-supervised fine-tuning with measurement consistency losses adapts to new imaging modalities using fewer annotated samples.Results:Achieves state-of-the-art performance on fastMRI(peak signal-to-noise ratio(PSNR):34.04 for single-coil/31.50 for multi-coil)and Lung Image Database Consortium and Image Database Resource Initiative(28.83 PSNR under Poisson noise).Clinical evaluations demonstrate superior preservation of anatomical structures,with SSIM improvements of 8.8%for single-coil and 4.36%for multi-coil MRI over uDPIR.Conclusion:It offers a flexible,efficient,and scalable solution for medical image reconstruction,addressing the challenges of noise,undersampling,and modality generalization.The model’s lightweight design allows for rapid inference,while its self-supervised fine-tuning capability minimizes reliance on large annotated datasets,making it suitable for real-world clinical applications.
文摘Raman imaging,as a molecular spectroscopy technique,has been widely studied and applied in research fields such as life sciences and food safety due to its excellent specificity and high resolution.However,its development still faces challenges such as weak signals,slow acquisition speed,and insufficient penetration depth.In recent years,the rapid development of aggregate science has provided new insights for addressing these limitations.Aggregation-induced emission(AIE)materials exhibit enhanced signals in the aggregated state,which may compensate for the inherent weak Raman signals.This article reviews the cutting-edge progress of Raman imaging technology and its current status in cross-disciplinary research with aggregate science,emphasizing the strategy of constructing AIE-Raman dual-responsive probes through molecular engineering to achieve functional complementarity between fluorescence localization and Raman quantification,thereby significantly improving detection sensitivity and specificity.These probes have demonstrated single-cell resolution and high spatiotemporal accuracy in applications such as tumor surgical navigation,diagnosis and treatment of drug-resistant bacteria,and dynamic monitoring of organelles.We also analyze the bottlenecks in this field,such as biological safety and the complexity of molecular design,and outline the future development directions,including intelligent responsive probes,artificial intelligence-assisted analysis,and multimodal fusion platforms.The integration of Raman imaging and AIE sheds new light in the field of medical imaging.
基金supported by the National Natural Science Foundation of China(61927813,61865009,12104203)Jiangxi Provincial Natu-ral Science Foundation(20212ACB201007)。
文摘Metasurfaces are artificial structures that can finely control the characteristics of electromagnetic waves at subwavelength scales,and they are widely used to manipulate the propagation,phase,amplitude,and polariza⁃tion of light.In this work,a bound state in the continuum(BIC)structure based on a metallic metasurface is pro⁃posed.By adjusting the metallic structure using CST and COMSOL software,a significant quasi-BIC peak can be achieved at a frequency of 0.8217 terahertz(THz).Through multi-level expansion analysis,it is found that the electric dipole(ED)is the main factor contributing to the resonant characteristics of the structure.By leveraging the characteristics of BIC,an imaging system was created and operated.According to the simulation results,the imaging system demonstrated excellent sensitivity and resolution,revealing the great potential of terahertz imag⁃ing.This research not only provides new ideas for the creation of BIC structures but also offers an effective refer⁃ence for the development of high-performance terahertz imaging technology.
文摘Two novel aggregation-induced emission(AIE)-active probes,TPA-H and TPA-2 F,were designed and synthesized based on a triphenylamine(TPA)core.Systematic characterization demonstrated that both probes exhibit excellent biocompatibility(cell viability>90%at concentrations up to 50μmol/L)and outstanding LD-targeting speci⁃ficity with minimal colocalization with other organelles such as mitochondria and lysosomes.During early differentia⁃tion of 3 T 3-L 1 adipocytes,both TPA-2 F and TPA-H clearly visualized small and nascent LDs that were difficult to be detected with BODIPY,indicating superior imaging sensitivity compared to the existing fluorescent probes for LDs.Moreover,TPA-2 F demonstrated exceptional photostability,retaining over 90%of its initial fluorescence intensity after 100 continuous laser scanning cycles,significantly outperforming TPA-H.This work not only provides two high-performance LD imaging tools but also highlights the potential of AIE luminogens(AIEgens)in organelle-specific bioimaging,offering promising avenues for early diagnosis and mechanistic research of lipid-related metabolic diseases.
基金support from the Kreitman School of Advanced Graduate Studies, Ben-Gurion University of the Negev。
文摘Neuromorphic cameras,or dynamic vision sensors,are bio-inspired event cameras that measure changes in the image brightness asynchronously and independently at the pixel level.Recently,they garnered increasing interest due to their extremely high temporal resolution,wide dynamic range,low power consumption,and high pixel bandwidth.Despite their advantages,most existing three-dimensional (3D) event imaging solutions rely on multicamera configurations,which are costly,complex,and challenging to synchronize.In this study,we introduce a new framework for four-dimensional (4D) event imaging using a single static neuromorphic camera.We take advantage of the inherent sparsity of event data to combine optically encoded stereo channels into a single event camera.By utilizing optical channel multiplexing,we maintain sensor resolution while retaining the key advantages of event cameras.
基金supported by National Natural Science Foundation of China (Nos.21906124,32302202)Natural Science Foundation of Hubei Province (No.2017CFB220)Natural Science Foundation of Shandong Province (No.ZR2023MH278)。
文摘Metal organic framework(MOF) assembled with coordination bonds has the disadvantage of poor stability that limits its application in the field of stationary phase,while covalent organic framework(COF)assembled through covalent bonds exhibits excellent structural stability.It has been shown that the stationary phases prepared by combining MOF and COF can make up for the poor stability of MOF@SiO_(2),and the MOF/COF composites have superior chromatographic separation performance.However,the traditional methods for preparing COF/MOF based stationary phases are generally solvent thermal synthesis.In this study,a green and low-cost synthesis method was proposed for the preparation of MOF/COF@SiO_(2) stationary phase.Firstly,COF@SiO_(2) was prepared in a choline chloride/ethylene glycol based deep eutectic solvent(DES).Secondly,another acid-base tunable DES prepared by mixing p-toluenesulfonic acid(PTSA)and 2-methylimidazole in different proportions was introduced as the reaction solvent and reactant for rapid synthesis of MOF/COF@SiO_(2).Compared with the toxic transition metal-based MOFs selected in most previous studies,a lightweight and non-toxic S-zone metal(calcium) based MOF was employed in this study.PTSA and calcium will form the calcium/oxygen-containing organic acid framework in acidic DES,which assembles with terephthalic acid dissolved in basic DES to form MOF.The strong hydrogen bonding effect of DES can facilitate rapid assembly of Ca-MOF.The obtained Ca-MOF/COF@SiO_(2) can be used for multi-mode chromatography to efficiently separate multiple isomeric/hydrophilic/hydrophobic analytes.The synthesis method of Ca-MOF/COF@SiO_(2) is green and mild,especially the use of acid-base tunable DES promotes the rapid synthesis of non-toxic Ca-MOF/COF@silica composites,which offers an innovative approach of greenly synthesizing novel MOF/COF stationary phases and extends their applications in the field of chromatography.
文摘Background:Sarcomatoid carcinoma of the ureter(SCU)is a highly aggressive and relatively uncommon malignant tumor of the urinary tract.Its frequency is quite low,and its prognosis is very bad when compared to other cancers of the urinary system.SCU clinical reports are still hard to come by.MRI and PEI/CT imaging of ureteral sarcomatoid cancer is presented in this case to promote diagnostic awareness and comprehension of the imaging characteristics of this uncommon illness.Method:The patient had ureteral sarcomatoid cancer,which was verified by pathological investigation after ureteroscopic biopsy.The patient’s clinical information,imaging results,surgical outcomes,and pathological findings were gathered.A retrospective study was carried out in combinationwith pertinent national and international literature.Results:An 84-year-old female patient was admitted for“left flank discomfort lasting over one month.”MRI revealed an irregular soft tissue mass in the middle-lower segment of the left ureter.T2-weighted imaging showed an unevenly slightly hyperintense signal.Diffusion-weighted imaging demonstrated restricted diffusion.Contrastenhanced imaging exhibited heterogeneous enhancement.PET/CT demonstrated significantly increased fluorodeoxyglucose metabolism in the mass with secondary left upper urinary tract obstruction.Concurrent findings included a solitary metastatic lesion in hepatic segment S6 and multiple lymph node metastases along the left common iliac and external iliac arteries.Preoperative diagnosis suggested a malignant tumor of the ureter.The patient underwent left nephroureteroscopy with biopsy,and the postoperative pathological diagnosis was ureteral sarcomatoid carcinoma.Conclusion:Ureteral sarcomatoid carcinoma is a rare,highly malignant,and aggressive tumor with nonspecific imaging features,typically presenting as an invasively growing mass.Diagnosis relies on postoperative pathology and immunohistochemical examination.MRI and PET/CT scans are valuable for preoperative localization and characterization,tumor staging,treatment planning,and postoperative follow-up.The prognosis is extremely negative.The main treatment option is radical surgery,although constant monitoring is necessary since early recurrence and metastases are frequent after surgery.
基金supported by the National Natural Science Foundation of China(Nos.82372116,U23A2097)Guangdong Basic and Applied Basic Research Foundation(No.2022A1515010620)+2 种基金Shenzhen Medical Research Fund(Nos.B2302047,A2302047)Shenzhen Science and Technology Program(No.JCYJ20220818095806014)Research Team Cultivation Program of Shenzhen University(No.2023QNT019).
文摘The level of glutathione(GSH)is significantly associated with numerous pathological processes,thus,real-time detection of the GSH level is of significance for early diagnosis of GSH-related diseases.Herein,we developed in vivo second near-infrared(NIR-II)window fluorescence(FL)and ratiometric photoacoustic(RPA)dual-modality imaging of GSH using a GSH-activatable probe(LET-14).LET-14 was synthesized based on a rhodamine hybrid xanthene skeleton with a FL shielding 2,4-dinitrobenzene sulfonyl group that can be specifically cleaved by GSH,thus resulting in a markedly bathochromic-shift absorption,a 6.5-fold increase in NIR-II FL intensity(FL_(920))and a 13-fold increase in RPA signal(PA_(880)/PA_(705))in vitro.Intriguingly,LET-14 exhibits good selectivity and sensitivity for NIR-II FL and RPA dual-modality imaging of GSH in 4T1 tumor-bearing mouse model.Our findings develop an in vivo detection tool of GSH,which has great potential in the field of cancer diagnosis.
基金supported by the National Key Research and Development Program of China(2022YFC2402400)the National Natural Science Foundation of China(82027803,62275062)+7 种基金the Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology(2020B121201010)the Shenzhen Science and Technology Innovation Committee under Grant(JCYJ20220818101417039)the Shenzhen Key Laboratory for Molecular lmaging(ZDSY20130401165820357)the Shenzhen Medical Research Fund(D2404002)the Project of Shandong Innovation and Startup Community of High-end Medical Apparatus and Instruments(2023-SGTTXM-002 and 2024-SGTTXM-005)the Shandong Province Technology Innovation Guidance Plan(Central Leading Local Science and Technology Development Fund)(YDZX2023115)the Taishan Scholar Special Funding Project of Shandong Provinceand the Shandong Laboratory of Advanced Biomaterials and Medical Devices in Weihai(ZL202402).
文摘The photoacoustic imaging of lipid is intrinsically constrained by the feeble nature of endogenous lipid signals,posing a persistent sensitivity challenge that demands innovative solutions.Although adopting high-efficiency excitation and detection elements may improve the imaging sensitivity to a certain extent,the application of the elements is inevitably subject to various limitations in practical applications,particularly during in vivo imaging and endoscopic imaging.In this study,we propose a multi-combinatorial approach to enhance the sensitivity of lipid photoacoustic imaging.The approach involves wavelet transform processing of one-dimensional A-line signals,gradient-based denoising of two-dimensional B-scan images,and finally,threedimensional spatial weighted averaging of the data processed by the previous two steps.This method not only significantly improves the signal-to-noise ratio(SNR)in distinguished feature regions of the image by around 10 dB,but also efficiently extracts weak signals with no distinct features in the original image.After processing with this method,the images acquired under single scanning were compared with those obtained under multiple scanning.The results showed highly consistent image features,with the structural similarity index increasing from 0.2 to 0.8,confirming the accuracy and reliability of the multi-combinatorial approach.
基金funded by the Deanship of Scientific Research(DSR)at King Abdulaziz University,Jeddah,under grant No.(IFPDP-261-22).
文摘Medical imaging is essential in modern health care,allowing accurate diagnosis and effective treatment planning.These images,however,often demonstrate low contrast,noise,and brightness distortion that reduce their diagnostic reliability.This review presents a structured and comprehensive analysis of advanced histogram equalization(HE)-based techniques for medical image enhancement.Our review methodology encompasses:(1)classical HE approaches and related limitations in medical domains;(2)adaptive schemes like Adaptive Histogram Equalization(AHE)and Contrast Limited Adaptive Histogrma Equalization(CLAHE)and their advance variants;(3)brightnesspreserving schemes like BBHE and MMBEBHE and related algorithms;(4)dynamic and recursive histogram equalization methods incorporating DHE and RMSHE;(5)fuzzy logic-based enhancement methodologies addressing uncertainty and noise in medical images;and(6)hybrid optimization methodologies through the application of metaheuristic algorithms(World Cup Optimization,Particle Swarm Optimization,Genetic Algorithms,along with histogram-based methodologies.)There is also a comparative discussion given based on contrast improvement,image brightness preservation,noise management,and computational efficiency.Such advancements have better capabilities of improving image quality,which is more important for improved diagnosis and image analysis.
基金supported by the National Natural Science Foundation of China(Grant No.42274225)the International Science and Technology Cooperation Project of the Ningbo Key R&D Program(Grant No.2024H031).
文摘Electrons in the energy range of 10–100 keV are important energetic particle components in the magnetosphere,and they play a key role in many physical processes in the magnetosphere.However,many scientific questions about these processes are still unanswered.High spatiotemporal and energy-resolution imaging detection of 10–100 keV electrons is of great significance for solving these scientific problems.The traditional space particle detection technology cannot effectively detect the medium-energy electrons in this energy range.In this project,we propose combining low-noise particle detection technology with pinhole imaging technology to achieve high-resolution imaging detection of 10–100 keV medium-energy electrons in the magnetosphere,and at the same time achieve miniaturization(≤3.2 kg and size of 150×150×170 mm)and low power consumption(≤5 W)of the instrument,which can be used for space physics research and space weather applications in the future.
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2022YFA1603601,2021YFF0601203,and 2021YFA1600703)。
文摘The unique advantage of x-ray ghost imaging(XGI)is its potential in low dose radiology.One of the practical ways to reduce the radiation exposure is to reduce the measurements while remaining sufficient image quality.Synthetic aperture x-ray ghost imaging(SAXGI)is invented to achieve megapixel XGI with limited measurements,which is expected to implement XGI simultaneously with large field of view and low radiation exposure.In this paper,we experimentally investigate the effect of measurements reduction on the spatial resolution and image quality of SAXGI with standard sample and biomedical specimen.The results with a resolution chart demonstrated that at 360 measurements,SAXGI successfully retrieved the sample image of 1960×1960 pixels with spatial resolution of 4μm.With measurement reduction,the spatial resolution deteriorates but the sparser structures are still discernable.Even with measurements reduced to 10,a spatial resolution of 10μm can still be achieved by SAXGI.A biomedical sample of a fish specimen is employed to evaluate the method and the fish image of 2000×1000 pixels with an SSIM of 0.962 is reconstructed by SAXGI with 770measurements,corresponding to an accumulative exposure reduction of more than 2 times.With the measurements reduced to 10 which corresponds to 1/160 of the accumulative radiation exposure for conventional radiology,bulky structure like the fish skeleton can still be definitely discerned and the SSIM for the reconstructed image still retained 0.9179.Results of this paper demonstrate that measurements reduction is practicable for the radiation exposure reduction of the sample,which implicates that SAXGI with limited measurements is an efficient solution for low dose radiology.
基金support from the National Natural Science Foundation of China(Grant Nos.52174313 and 52304350)thank all members of the Hebei High Quality Steel Continuous Casting Engineering Technology Research Center at North China University of Science and Technology,Tangshan,China.
文摘The flow behavior of molten steel in the thin slab mold under high casting speed conditions was investigated,with a focus on the multi-mode continuous casting and rolling mold.A steel-slag two-phase flow model was established using large eddy simulation,the volume of fluid,and magnetohydrodynamics methods through numerical simulation.The maximum flow velocity and wave height at the steel-slag interface within the mold are critical evaluation criteria for analyzing asymmetric flow under varying casting speeds and electromagnetic braking.The results indicate that the asymmetric flows within the mold do not occur synchronously.The severity of the asymmetric flow correlates with the velocity difference across the steel-slag interface.A greater biased flow prolongs the time required to revert to a steady state.When the magnetic field intensity is set to 0.24 T and the magnetic pole position is at 390 mm from the steel-slag interface,this configuration can reduce the velocity of the steel-slag interface,thereby mitigating the asymmetric flow.Additionally,it can diminish the velocity,impact depth,and impact intensity on the narrow face of the jet,thus improving the distribution of velocity and turbulent kinetic energy within the mold.This configuration prolongs the time required for the steel-slag interface to transition from a stable state to its maximum velocity and shortens the time for the interface to return to stability from an unstable state.Moreover,it ensures the positional stability of the steel-slag interface,confining its position within−3 mm.
基金supported and funded by the Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2601).
文摘Generative Adversarial Networks(GANs)have become valuable tools in medical imaging,enabling realistic image synthesis for enhancement,augmentation,and restoration.However,their integration into clinical workflows raises concerns,particularly the risk of subtle distortions or hallucinations that may undermine diagnostic accuracy and weaken trust in AI-assisted decision-making.To address this challenge,we propose a hybrid deep learning framework designed to detect GAN-induced artifacts in medical images,thereby reinforcing the reliability of AI-driven diagnostics.The framework integrates low-level statistical descriptors,including high-frequency residuals and Gray-Level Co-occurrence Matrix(GLCM)texture features,with high-level semantic representations extracted from a pre-trained ResNet18.This dual-stream approach enables detection of both pixel-level anomalies and structural inconsistencies introduced by GAN-based manipulation.We validated the framework on a curated dataset of 10,000 medical images,evenly split between authentic and GAN-generated samples across four modalities:MRI,CT,X-ray,and fundus photography.To improve generalizability to real-world clinical settings,we incorporated domain adaptation strategies such as adversarial training and style transfer,reducing domain shift by 15%.Experimental results demonstrate robust performance,achieving 92.6%accuracy and an F1-score of 0.91 on synthetic test data,and maintaining strong performance on real-world GAN-modified images with 87.3%accuracy and an F1-score of 0.85.Additionally,the model attained an AUC of 0.96 and an average precision of 0.92,outperforming conventional GAN detection pipelines and baseline Convolutional Neural Network(CNN)architectures.These findings establish the proposed framework as an effective and reliable solution for detecting GAN-induced hallucinations in medical imaging,representing an important step toward building trustworthy and clinically deployable AI systems.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB0530000)the Discipline Construction Foundation of“Double World-class Project”.
文摘Laser wakefield accelerators(LWFAs)offer acceleration gradients up to 1000 times higher than those of conventional radio-frequency accelerators,offering a pathway to significantly more compact and cost-effective accelerator systems.This breakthrough opens up new possibilities for laboratory-scale light sources.All-optical inverse Compton scattering(AOCS)sources driven by LWFAs produce high-brightness,quasimonochromatic X rays with micrometer-scale source sizes,delivering the spatial coherence and resolution required for X-ray phase-contrast imaging(XPCI).These features position AOCS X-ray sources as promising tools for applications in biology,medicine,physics,and materials science.However,previous AOCS-based imaging studies have primarily focused on X-ray absorption imaging.In this work,we report successful experimental demonstrations of edge-enhanced in-line XPCI using energy-tunable,quasi-monochromatic AOCS X rays.With a spatial resolution of~20μm,our results clearly show the potential of high-resolution,AOCS-based XPCI applications.
基金funding this work through Ongoing Research Funding Program,(ORF-2025-704)King Saud University,Riyadh,Saudi Arabia.
文摘Brain tumours disrupt the normal functioning of the brain and,if left untreated,can invade surrounding tissues,blood vessels,and nerves,posing a severe threat.Consequently,early detection is crucial to prevent tragic outcomes.Distinguishing brain tumours through manual detection poses a significant challenge given their diverse features,such as differing shapes,sizes,and nucleus characteristics.Therefore,this research introduces an improved architecture for tumour detection named as Brain-RetinaNet,an extension of the RetinaNet model.Brain-RetinaNet is specifically designed for automated detection and identification of brain tumours in MRI images.It utilises an advanced multiscale feature fusion mechanism within the X-module,complemented by the channel attention module.The feature fusion mechanism within the X-module progressively merges features from different scales,producing enriched feature maps that encompass valuable information.At the same time,the attention module dynamically allocates optimal weights to individual channels within the feature map,enabling the network to prioritise relevant features while reducing interference from unnecessary ones.Moreover,this study employs data augmentation technique to address the limitation of a limited number of available samples.Experimental results indicate that Brain-RetinaNet outperforms existing detectors such as YOLO,SSD,Centernet,EfficientNet,and M2det for the brain tumour detection from MRI images.
基金funded by the Natural Science Foundation of Shanghai Municipality(No.21ZR1440500)the Shanghai Science and Technology Commission(Grant No.21S31902700).
文摘In recent years,the rapid advancement of artificial intelligence(AI)technology has enabled AI-assisted negative screening to significantly enhance physicians'efficiency through image feature analysis and multimodal data modeling,allowing them to focus more on diagnosing positive cases.Meanwhile,multispectral imaging(MSI)integrates spectral and spatial resolution to capture subtle tissue features invisible to the human eye,providing high-resolution data support for pathological analysis.Combining AI technology with MSI and employing quantitative methods to analyze multiband biomarkers(such as absorbance differences in keratin pearls)can effectively improve diagnostic specificity and reduce subjective errors in manual slide interpretation.To address the challenge of identifying negative tissue sections,we developed a discrimination algorithm powered by MSI.We demonstrated its efficacy using cutaneous squamous cell carcinoma(cSCC)as a representative case study.The algorithm achieved 100%accuracy in excluding negative cases and effectively mitigated the false-positive problem caused by cSCC heterogeneity.We constructed a multispectral image(MSI)dataset acquired at 520 nm,600 nm,and 630 nm wavelengths.Subsequently,we employed an optimized MobileViT model for tissue classification and performed comparative analyses against other models.The experimental results showed that our optimized MobileViT model achieved superior performance in identifying negative tissue sections,with a perfect accuracy rate of 100%.Thus,our results confirm the feasibility of integrating MSI with AI to exclude negative cases with perfect accuracy,offering a novel solution to alleviate the workload of pathologists.
基金supported by the National Natural Science Foundation of China(T2421003/22327802/41806142)Guangdong Basic and Applied Basic Foundation(2025A1515011484/2022A1515011845)+1 种基金Shenzhen Key Laboratory of Photonics and Biophotonics(ZDSYS20210623092006020)Medical-Engineering Interdisciplinary Research Foundation of Shenzhen University(2023YG033).
文摘Optical imaging has been pivotal in biological research(e.g.,cellular/developmental biology)for over two centuries.Recent advances like super-resolution fluorescence and nonlinear optical microscopy enable nanoscale studies of live cells and animals,yet their application to marine mollusks-key marine ecosystem species,remains underexplored.This review summarizes optical imaging techniques and their use in investigating marine mollusks across molecular,cellular,tissue,and individual levels.It highlights promising avenues for novel imaging methods to unravel the structures and functions of these organisms in future research,with a focus on advancements in applying cutting-edge optical techniques across these hierarchical levels.Given optical imaging's significance in elucidating marine mollusks'ecological and genetic information,this field deserves substantial attention and support.The review aims to address existing gaps,providing researchers and practitioners with comprehensive insights to foster further progress in this domain.
基金supported by the National Natural Science Foundation of China (Grant Nos. 62405231, 62405235, and 62575229)the National Key Laboratory of Space Target Awareness (Grant Nos. STA2024KGL0203, STA2024ZCA0203, and STA-24-04-05)+3 种基金the Beijing Key Laboratory of Advanced Optical Remote Sensing Technology (Grant No. AORS202405)the China Postdoctoral Science Foundation (Grant No. 2024M762527)the Shaanxi Province High-level Innovation and Entrepreneurship Talent Program (Grant No. H02439005)the Natural Science Foundation of Shaanxi (Grant Nos. S2024-JC-JCQN-60, S2025-JCQYTS-0107, and 2025JC-QYCX-05)。
文摘In complex media scattering,multiple scattering severely degrades the optical wavefront and results in blurred images,while the spectral distortion caused by the scattering effect leads to severe color distortion.Achieving color high-resolution imaging through scattering media remains a significant challenge.Here,we propose a broadband,polarization-based method for color high-resolution imaging through scattering media.This approach enables high-resolution reconstruction by effectively separating the speckle illumination pattern from the mixed-scattering field information,leveraging polarization common-mode characteristics.Concurrently,it incorporates chromatic balance compensation to correct spectral aliasing in the scattered light field,enabling color high-resolution imaging through complex scattering media.To further optimize color distortion caused by scattering,a compensation strategy combining color constancy and white balance theory is adopted.Experimental results demonstrate that the proposed method significantly enhances both spatial resolution and color fidelity across various scattering conditions and target materials,showcasing strong adaptability and robustness.This approach provides an effective solution for achieving high-resolution color optical imaging in complex scattering environments.
