Integrating multiple medical imaging techniques,including Magnetic Resonance Imaging(MRI),Computed Tomography,Positron Emission Tomography(PET),and ultrasound,provides a comprehensive view of the patient health status...Integrating multiple medical imaging techniques,including Magnetic Resonance Imaging(MRI),Computed Tomography,Positron Emission Tomography(PET),and ultrasound,provides a comprehensive view of the patient health status.Each of these methods contributes unique diagnostic insights,enhancing the overall assessment of patient condition.Nevertheless,the amalgamation of data from multiple modalities presents difficulties due to disparities in resolution,data collection methods,and noise levels.While traditional models like Convolutional Neural Networks(CNNs)excel in single-modality tasks,they struggle to handle multi-modal complexities,lacking the capacity to model global relationships.This research presents a novel approach for examining multi-modal medical imagery using a transformer-based system.The framework employs self-attention and cross-attention mechanisms to synchronize and integrate features across various modalities.Additionally,it shows resilience to variations in noise and image quality,making it adaptable for real-time clinical use.To address the computational hurdles linked to transformer models,particularly in real-time clinical applications in resource-constrained environments,several optimization techniques have been integrated to boost scalability and efficiency.Initially,a streamlined transformer architecture was adopted to minimize the computational load while maintaining model effectiveness.Methods such as model pruning,quantization,and knowledge distillation have been applied to reduce the parameter count and enhance the inference speed.Furthermore,efficient attention mechanisms such as linear or sparse attention were employed to alleviate the substantial memory and processing requirements of traditional self-attention operations.For further deployment optimization,researchers have implemented hardware-aware acceleration strategies,including the use of TensorRT and ONNX-based model compression,to ensure efficient execution on edge devices.These optimizations allow the approach to function effectively in real-time clinical settings,ensuring viability even in environments with limited resources.Future research directions include integrating non-imaging data to facilitate personalized treatment and enhancing computational efficiency for implementation in resource-limited environments.This study highlights the transformative potential of transformer models in multi-modal medical imaging,offering improvements in diagnostic accuracy and patient care outcomes.展开更多
BACKGROUND Congestive hepatopathy,also known as nutmeg liver,is liver damage secondary to chronic heart failure(HF).Its morphological characteristics in terms of medical imaging are not defined and remain unclear.AIM ...BACKGROUND Congestive hepatopathy,also known as nutmeg liver,is liver damage secondary to chronic heart failure(HF).Its morphological characteristics in terms of medical imaging are not defined and remain unclear.AIM To leverage machine learning to capture imaging features of congestive hepatopathy using incidentally acquired computed tomography(CT)scans.METHODS We retrospectively analyzed 179 chronic HF patients who underwent echocardiography and CT within one year.Right HF severity was classified into three grades.Liver CT images at the paraumbilical vein level were used to develop a ResNet-based machine learning model to predict tricuspid regurgitation(TR)severity.Model accuracy was compared with that of six gastroenterology and four radiology experts.RESULTS In the included patients,120 were male(mean age:73.1±14.4 years).The accuracy of the results predicting TR severity from a single CT image for the machine learning model was significantly higher than the average accuracy of the experts.The model was found to be exceptionally reliable for predicting severe TR.CONCLUSION Deep learning models,particularly those using ResNet architectures,can help identify morphological changes associated with TR severity,aiding in early liver dysfunction detection in patients with HF,thereby improving outcomes.展开更多
Corporate image is the external manifestation of a company’s cultural and spiritual essence,as well as the overall impression formed through its interactions with the public.Huawei,as a successful multinational enter...Corporate image is the external manifestation of a company’s cultural and spiritual essence,as well as the overall impression formed through its interactions with the public.Huawei,as a successful multinational enterprise,has established a robust corporate image in the international market through technological innovation and brand building.Moreover,Huawei’s development is closely aligned with national policies and strategies,making it a representative enterprise for showcasing China’s technological independence and national image.This study examines Huawei’s English press releases on product launches published between 2022 and 2024 and conducts a comparative analysis with similar materials from Apple’s official website.Based on Fairclough’s three-dimensional discourse analysis model,this research explores the linguistic features of Huawei’s corporate image construction from the perspectives of text,discourse practice,and social practice.The findings reveal that Huawei has successfully constructed a corporate image that emphasizes technological innovation,prioritizes user needs,and underscores its identity as a national enterprise.This study not only sheds light on Huawei’s strategies for image construction in international competition but also provides a valuable reference for Chinese enterprises in their cultural communication and brand building during the globalization process.展开更多
Given the importance of sentiment analysis in diverse environments,various methods are used for image sentiment analysis,including contextual sentiment analysis that utilizes character and scene relationships.However,...Given the importance of sentiment analysis in diverse environments,various methods are used for image sentiment analysis,including contextual sentiment analysis that utilizes character and scene relationships.However,most existing works employ character faces in conjunction with context,yet lack the capacity to analyze the emotions of characters in unconstrained environments,such as when their faces are obscured or blurred.Accordingly,this article presents the Adaptive Multi-Channel Sentiment Analysis Network(AMSA),a contextual image sentiment analysis framework,which consists of three channels:body,face,and context.AMSA employs Multi-task Cascaded Convolutional Networks(MTCNN)to detect faces within body frames;if detected,facial features are extracted and fused with body and context information for emotion recognition.If not,the model leverages body and context features alone.Meanwhile,to address class imbalance in the EMOTIC dataset,Focal Loss is introduced to improve classification performance,especially for minority emotion categories.Experimental results have shown that certain sentiment categories with lower representation in the dataset demonstrate leading classification accuracy,the AMSA yields a 2.53%increase compared with state-of-the-art methods.展开更多
Applying visual grammar theory,this study examines representational,interactive,and compositional meanings of the giant panda in Western media cartoons related to China from 1999 to the present.Distinct phases in the ...Applying visual grammar theory,this study examines representational,interactive,and compositional meanings of the giant panda in Western media cartoons related to China from 1999 to the present.Distinct phases in the panda’s representation were identified and illustrated by cases of cartoons in major Western media.These phases trace shift of panda cartoon image from a symbol of peace and friendliness to a politicized emblem of China’s international stance.Key visual trends,such as transitivity,color symbolism,scale enlargement,and increasing compositional complexity,embody the panda’s role in shaping China’s global image and its function in international discourse.These trends reflect the panda’s transformation into a contested symbol,which mediates between China’s self-representation and Western perceptions of its geopolitical rise.By situating the analysis within the context of China’s growing global influence,this study contributes to visual and media studies,demonstrating how cultural symbols are recontextualized to reflect and shape geopolitical narratives.展开更多
Methods and procedures of three-dimensional （3D） characterization of the pore structure features in the packed ore particle bed are focused. X-ray computed tomography was applied to deriving the cross-sectional imag...Methods and procedures of three-dimensional （3D） characterization of the pore structure features in the packed ore particle bed are focused. X-ray computed tomography was applied to deriving the cross-sectional images of specimens with single particle size of 1-2, 2-3, 3-4, 4-5, 5-6, 6-7, 7-8, 8-9, 9-10 ram. Based on the in-house developed 3D image analysis programs using Matlab, the volume porosity, pore size distribution and degree of connectivity were calculated and analyzed in detail. The results indicate that the volume porosity, the mean diameter of pores and the effective pore size （d50） increase with the increasing of particle size. Lognormal distribution or Gauss distribution is mostly suitable to model the pore size distribution. The degree of connectivity investigated on the basis of cluster-labeling algorithm also increases with increasing the particle size approximately.展开更多
To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation f...To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation for input image with angle difference between them. A hi erarchical feature matching algorithm was adopted to get the final transform parameters between the two images. The simulation results for two infrared images show that the method can effectively, quickly and accurately register images and be antinoise to some extent.展开更多
AIM:To summarize publication trends in the field of strabismus over the past 30y and predict future research hotspots.METHODS:A total of 2915 English-language articles and reviews on strabismus,published between 1993 ...AIM:To summarize publication trends in the field of strabismus over the past 30y and predict future research hotspots.METHODS:A total of 2915 English-language articles and reviews on strabismus,published between 1993 and 2022,were retrieved from the Web of Science Core Collection.Bibliometric analyses were performed using VOSviewer and CiteSpace software to explore publication trends,as well as the contributions and collaborative networks of countries/regions,authors,institutions,and journals.RESULTS:The annual number of publications on strabismus showed a consistent upward trend.The United States(USA)maintained a leading position in this research field while Republic of Korea and China emerged as rapidly advancing contributors over the last decade.The University of California,Los Angeles ranked as the most productive institution,and Jonathan M.Holmes from USA was the most productive author.Journal of AAPOS was the leading journal with the most strabismus publications,whereas the two most highly cited articles were both published in Ophthalmology.Co-occurrence analysis identified pivotal keywords and burst terms,including intermittent exotropia(IXT),acute acquired comitant esotropia(AACE),functional magnetic resonance imaging(fMRI),and surgical treatment,which were confirmed as predominant and frontier topics.CONCLUSION:This study provides a comprehensive bibliometric analysis of strabismus research,revealing the evolution of research hotspots over the past 30y and outlining several cutting-edge directions for future investigation.展开更多
Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination...Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.展开更多
BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features ...BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features is crucial for early detection and appropriate treatment planning.AIM To retrospectively analyze the relationship between different pathological types of pancreatic cancer and their corresponding imaging features.METHODS We retrospectively analyzed the data of 500 patients diagnosed with pancreatic cancer between January 2010 and December 2020 at our institution.Pathological types were determined by histopathological examination of the surgical spe-cimens or biopsy samples.The imaging features were assessed using computed tomography,magnetic resonance imaging,and endoscopic ultrasound.Statistical analyses were performed to identify significant associations between pathological types and specific imaging characteristics.RESULTS There were 320(64%)cases of pancreatic ductal adenocarcinoma,75(15%)of intraductal papillary mucinous neoplasms,50(10%)of neuroendocrine tumors,and 55(11%)of other rare types.Distinct imaging features were identified in each pathological type.Pancreatic ductal adenocarcinoma typically presents as a hypodense mass with poorly defined borders on computed tomography,whereas intraductal papillary mucinous neoplasms present as characteristic cystic lesions with mural nodules.Neuroendocrine tumors often appear as hypervascular lesions in contrast-enhanced imaging.Statistical analysis revealed significant correlations between specific imaging features and pathological types(P<0.001).CONCLUSION This study demonstrated a strong association between the pathological types of pancreatic cancer and imaging features.These findings can enhance the accuracy of noninvasive diagnosis and guide personalized treatment approaches.展开更多
BACKGROUND It is evident that an accurate evaluation of T and N stage rectal cancer is essential for treatment planning.It has not been extensively investigated whether texture features derived from diffusion-weighted...BACKGROUND It is evident that an accurate evaluation of T and N stage rectal cancer is essential for treatment planning.It has not been extensively investigated whether texture features derived from diffusion-weighted imaging(DWI)images and apparent diffusion coefficient(ADC)maps are associated with the extent of local invasion(pathological stage T1-2 vs T3-4)and nodal involvement(pathological stage N0 vs N1-2)in rectal cancer.AIM To predict different stages of rectal cancer using texture analysis based on DWI images and ADC maps.METHODS One hundred and fifteen patients with pathologically proven rectal cancer,who underwent preoperative magnetic resonance imaging,including DWI,were enrolled,retrospectively.The ADC measurements(ADCmean,ADCmin,ADCmax)as well as texture features,including the gray level co-occurrence matrix parameters,the gray level run-length matrix parameters and wavelet parameters were calculated based on DWI(b=0 and b=1000)images and the ADC maps.Independent sample t-tests or Mann-Whitney U tests were used for statistical analysis.Multivariate logistic regression analysis was conducted to establish the models.The predictive performance was validated by receiver operating characteristic curve analysis.RESULTS Dissimilarity,sum average,information correlation and run-length nonuniformity from DWIb=0 images,gray level nonuniformity,run percentage and run-length nonuniformity from DWIb=1000 images,and dissimilarity and run percentage from ADC maps were found to be independent predictors of local invasion(stage T3-4).The area under the operating characteristic curve of the model reached 0.793 with a sensitivity of 78.57%and a specificity of 74.19%.Sum average,gray level nonuniformity and the horizontal components of symlet transform(SymletH)from DWIb=0 images,sum average,information correlation,long run low gray level emphasis and SymletH from DWIb=1000 images,and ADCmax,ADCmean and information correlation from ADC maps were identified as independent predictors of nodal involvement.The area under the operating characteristic curve of the model reached 0.802 with a sensitivity of 80.77%and a specificity of 68.25%.CONCLUSION Texture features extracted from DWI images and ADC maps are useful clues for predicting pathological T and N stages in rectal cancer.展开更多
Confocal laser endomicroscopy(CLE)has become an indispensable tool in the diagnosis and detection of gastrointestinal(GI)diseases due to its high-resolution and high-contrast imaging capabilities.However,the early-sta...Confocal laser endomicroscopy(CLE)has become an indispensable tool in the diagnosis and detection of gastrointestinal(GI)diseases due to its high-resolution and high-contrast imaging capabilities.However,the early-stage imaging changes of gastrointestinal disorders are often subtle,and traditional medical image analysis methods rely heavily on manual interpretation,which is time-consuming,subject to observer variability,and inefficient for accurate lesion identification across large-scale image datasets.With the introduction of artificial intelligence(AI)technologies,AI-driven CLE image analysis systems can automatically extract pathological features and have demonstrated significant clinical value in lesion recognition,classification diagnosis,and malignancy prediction of GI diseases.These systems greatly enhance diagnostic efficiency and early detection capabilities.This review summarizes the applications of AI-assisted CLE in GI diseases,analyzes the limitations of current technologies,and explores future research directions.It is expected that the deep integration of AI and confocal imaging technologies will provide strong support for precision diagnosis and personalized treatment in the field of gastrointestinal disorders.展开更多
We present two haze removal algorithms for single image based on haziness analysis.One algorithm regards haze as the veil layer,and the other takes haze as the transmission.The former uses the illumination component i...We present two haze removal algorithms for single image based on haziness analysis.One algorithm regards haze as the veil layer,and the other takes haze as the transmission.The former uses the illumination component image obtained by retinex algorithm and the depth information of the original image to remove the veil layer.The latter employs guided filter to obtain the refined haze transmission and separates it from the original image.The main advantages of the proposed methods are that no user interaction is needed and the computing speed is relatively fast.A comparative study and quantitative evaluation with some main existing algorithms demonstrate that similar even better quality results can be obtained by the proposed methods.On the top of haze removal,several applications of the haze transmission including image refocusing,haze simulation,relighting and 2-dimensional(2D)to 3-dimensional(3D) stereoscopic conversion are also implemented.展开更多
on the basis of analyzing the characteristics of low light level(LLL)image and ultra-violet image and the information amount of dual channel color night vision system,the LLL and ultra-violet color night vision techni...on the basis of analyzing the characteristics of low light level(LLL)image and ultra-violet image and the information amount of dual channel color night vision system,the LLL and ultra-violet color night vision technique is put forward.The methods of gray-scale modulation,frequency field fusion,special component fusion arc tried,and the improved LLL and ultra-violet image pseudo color fusion algorithms are presented.These new algorithms include subsection gray-scale modulation,image difference picking-up,component separation based on the reflected characteristics to night skylight reflection characteristics of objects and color space mapping which embodies the spectrum response of image sensor and nature vision.Some good results are obtained.展开更多
Multi-modality medical image fusion has more and more important applications in medical image analysis and understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fuse ...Multi-modality medical image fusion has more and more important applications in medical image analysis and understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fuse medical images from different modalities such as PET-MRI and CT-MRI. In particular, we evaluate the different fusion results when applying different selection rules and obtain optimum combination of fusion parameters.展开更多
Ultrasonic imaging logging provides continuous and oriented images of structures vs. depth. In the Chinese Continental Scientific Drilling (CCSD) Project, acoustic borehole images were recorded in the second pre-pilot...Ultrasonic imaging logging provides continuous and oriented images of structures vs. depth. In the Chinese Continental Scientific Drilling (CCSD) Project, acoustic borehole images were recorded in the second pre-pilot drillhole which penetrates the metamorphic rocks. This paper focuses on fracture evaluation of the drillhole with these images. Both least square fit and a modified Hough transform are used for fracture extraction, and 269 fractures were mapped in the interval from 69.5 to 1 020 m. Most fractures dip steeply, with an average angle of 54°. Fracture dip directions are dominantly in the range of 220°-280° above the depth of 267 m, but 80°-120° in the lower zones. These observations may indicate the differences in structural movements or in-situ stress fields between the upper and lower zones in the drillhole.展开更多
This paper delineates the images of Jiangxi Province as tourist destination perceived by about 2000 sample visitors at Lushan Mountain and other 3 famous resorts (Jinggangshan Mountains, Longhushan Mountain, and Sanqi...This paper delineates the images of Jiangxi Province as tourist destination perceived by about 2000 sample visitors at Lushan Mountain and other 3 famous resorts (Jinggangshan Mountains, Longhushan Mountain, and Sanqingshan Mountain), with a result that the most common image is the famous scenic mountain image with partial attribute of image of religious culture destination. In order to reveal the similarities and dissimilarities of images among the four destinations, a correspondence analysis on 16 image attributes was employed. The results indicate that the tourists’ images on Longhushan Mountain, Sanqingshan Mountain and Lushan Mountain are very similar: having a lot of good tourist sites, famous mountain scenery, being close to nature and having good guide service, and others, but religious culture and good shopping facilities having not made deep impression on tourist, while Jinggangshan Mountains is famous for its red culture. The correspondence analysis visualizes the strengths and weaknesses of the destinations, which is useful for market positioning among the competitive places. Finally, some marketing suggestions for the four destinations were provided.展开更多
Wavelet-fractal based SAR （synthetic aperture radar） image processing is one of the advanced technologies in image processing. The main concept of analysis is that after wavelet transformation, multifractal spectrum...Wavelet-fractal based SAR （synthetic aperture radar） image processing is one of the advanced technologies in image processing. The main concept of analysis is that after wavelet transformation, multifractal spectrum of the signal is different from that of noise. This difference is used to alleviate the noise produced by SAR image.The method to denoise SAR image using the process based on wavelet-fractai analysis is discussed in detail. Essentially, the present method focuses on adjusting the Hoelder exponent α of multifractal spectrum. After simulation, α should be adjusted to 1.72-1.73. The more the value of α exceeds 1.73, the less distinctive the edges of SAR image become. According to the authors denoising is optimal at α=1.72-1.73. In other words, when α =1.72-1.73, a smooth and denoised SAR image is produced.展开更多
The aim of the present study was to compare assessments of sperm concentration and sperm motility analysed by conventional semen analysis with those obtained by computer-assisted semen analysis （CASA） （Copenhagen R...The aim of the present study was to compare assessments of sperm concentration and sperm motility analysed by conventional semen analysis with those obtained by computer-assisted semen analysis （CASA） （Copenhagen Rigshospitalet Image House Sperm Motility Analysis System （CRISMAS） 4.6 software） using semen samples from 166 young Danish men. The CRISMAS software identifies sperm concentration and classifies spermatozoa into three motility categories. To enable comparison of the two methods, the four motility stages obtained by conventional semen analysis were, based on their velocity classifications, divided into three stages, comparable to the three CRISMAS motility categories： rapidly progressive （A）, slowly progressive （B） and non-progressive （C＋ D）. Differences between the two methods were large for all investigated parameters （P〈0.001）. CRISMAS overestimated sperm concentration and the proportion of rapidly progressive spermatozoa and, consequently, underestimated the percentages of slowly progressive and non-progressive spermatozoa, compared to the conventional method. To investigate whether results drifted according to time of semen analysis, results were pooled into quarters according to date of semen analysis. CRISMAS motility results appeared more stable over time compared to the conventional analysis; however, neither method showed any trends. Apparently, CRISMAS CASA results and results from the conventional method were not comparable with respect to sperm concentration and motility analysis. This needs to be accounted for in clinics using this software and in studies of determinants of these semen characteristics.展开更多
It is critical to establish a direct and precise method with a high sensitivity and selectivity in analytical chemistry. In this research, making use of a well known phenomenon of capillary flow, we have proposed an...It is critical to establish a direct and precise method with a high sensitivity and selectivity in analytical chemistry. In this research, making use of a well known phenomenon of capillary flow, we have proposed an image analysis method of nucleic acids at the price of a small amount of sample. When a droplet of the supramolecular complex solution, formed by neutral red and nucleic acids(NA) under an approximate neutral condition, was placed on the hydrophobic surface of dimethyl dichlorosilane pretreated glass slides, and it was evaporated, the supramolecular complex exhibited the periphery of the droplet due to the capillary effect, and accumulated there to form a red capillary flow directed assembly ring(CFDAR). A typical CFDAR has an outer diameter of (2 r ) about 1.18 mm and a ring width(2 δ ) of about 41 μm. Depending on the experimental conditions, a variety of CFDAR can be assembled. The experimental results are in agreement with our former theoretical discussion. It was found that when a droplet volume is 0.1 μL, the fluorescence intensity of the CFDAR formed by the NR NA is in proportion to the content of calf thymus DNA in the range of 0-0.28 ng, fish sperm DNA of 0-0.24 ng and yeast RNA of 0-0.16 ng with the limit of detection(3 σ ) of 1 7, 1.4 and 0.9 pg, respectively for the three nucleic acids.展开更多
基金supported by the Deanship of Research and Graduate Studies at King Khalid University under Small Research Project grant number RGP1/139/45.
文摘Integrating multiple medical imaging techniques,including Magnetic Resonance Imaging(MRI),Computed Tomography,Positron Emission Tomography(PET),and ultrasound,provides a comprehensive view of the patient health status.Each of these methods contributes unique diagnostic insights,enhancing the overall assessment of patient condition.Nevertheless,the amalgamation of data from multiple modalities presents difficulties due to disparities in resolution,data collection methods,and noise levels.While traditional models like Convolutional Neural Networks(CNNs)excel in single-modality tasks,they struggle to handle multi-modal complexities,lacking the capacity to model global relationships.This research presents a novel approach for examining multi-modal medical imagery using a transformer-based system.The framework employs self-attention and cross-attention mechanisms to synchronize and integrate features across various modalities.Additionally,it shows resilience to variations in noise and image quality,making it adaptable for real-time clinical use.To address the computational hurdles linked to transformer models,particularly in real-time clinical applications in resource-constrained environments,several optimization techniques have been integrated to boost scalability and efficiency.Initially,a streamlined transformer architecture was adopted to minimize the computational load while maintaining model effectiveness.Methods such as model pruning,quantization,and knowledge distillation have been applied to reduce the parameter count and enhance the inference speed.Furthermore,efficient attention mechanisms such as linear or sparse attention were employed to alleviate the substantial memory and processing requirements of traditional self-attention operations.For further deployment optimization,researchers have implemented hardware-aware acceleration strategies,including the use of TensorRT and ONNX-based model compression,to ensure efficient execution on edge devices.These optimizations allow the approach to function effectively in real-time clinical settings,ensuring viability even in environments with limited resources.Future research directions include integrating non-imaging data to facilitate personalized treatment and enhancing computational efficiency for implementation in resource-limited environments.This study highlights the transformative potential of transformer models in multi-modal medical imaging,offering improvements in diagnostic accuracy and patient care outcomes.
基金Supported by Grant-in-Aid for Research on Hepatitis from the Japan Agency for Medical Research and Development,No.24fk0210128h0002Grant-in-Aid for Scientific Research,No.KAKENHI-23K07372.
文摘BACKGROUND Congestive hepatopathy,also known as nutmeg liver,is liver damage secondary to chronic heart failure(HF).Its morphological characteristics in terms of medical imaging are not defined and remain unclear.AIM To leverage machine learning to capture imaging features of congestive hepatopathy using incidentally acquired computed tomography(CT)scans.METHODS We retrospectively analyzed 179 chronic HF patients who underwent echocardiography and CT within one year.Right HF severity was classified into three grades.Liver CT images at the paraumbilical vein level were used to develop a ResNet-based machine learning model to predict tricuspid regurgitation(TR)severity.Model accuracy was compared with that of six gastroenterology and four radiology experts.RESULTS In the included patients,120 were male(mean age:73.1±14.4 years).The accuracy of the results predicting TR severity from a single CT image for the machine learning model was significantly higher than the average accuracy of the experts.The model was found to be exceptionally reliable for predicting severe TR.CONCLUSION Deep learning models,particularly those using ResNet architectures,can help identify morphological changes associated with TR severity,aiding in early liver dysfunction detection in patients with HF,thereby improving outcomes.
文摘Corporate image is the external manifestation of a company’s cultural and spiritual essence,as well as the overall impression formed through its interactions with the public.Huawei,as a successful multinational enterprise,has established a robust corporate image in the international market through technological innovation and brand building.Moreover,Huawei’s development is closely aligned with national policies and strategies,making it a representative enterprise for showcasing China’s technological independence and national image.This study examines Huawei’s English press releases on product launches published between 2022 and 2024 and conducts a comparative analysis with similar materials from Apple’s official website.Based on Fairclough’s three-dimensional discourse analysis model,this research explores the linguistic features of Huawei’s corporate image construction from the perspectives of text,discourse practice,and social practice.The findings reveal that Huawei has successfully constructed a corporate image that emphasizes technological innovation,prioritizes user needs,and underscores its identity as a national enterprise.This study not only sheds light on Huawei’s strategies for image construction in international competition but also provides a valuable reference for Chinese enterprises in their cultural communication and brand building during the globalization process.
文摘Given the importance of sentiment analysis in diverse environments,various methods are used for image sentiment analysis,including contextual sentiment analysis that utilizes character and scene relationships.However,most existing works employ character faces in conjunction with context,yet lack the capacity to analyze the emotions of characters in unconstrained environments,such as when their faces are obscured or blurred.Accordingly,this article presents the Adaptive Multi-Channel Sentiment Analysis Network(AMSA),a contextual image sentiment analysis framework,which consists of three channels:body,face,and context.AMSA employs Multi-task Cascaded Convolutional Networks(MTCNN)to detect faces within body frames;if detected,facial features are extracted and fused with body and context information for emotion recognition.If not,the model leverages body and context features alone.Meanwhile,to address class imbalance in the EMOTIC dataset,Focal Loss is introduced to improve classification performance,especially for minority emotion categories.Experimental results have shown that certain sentiment categories with lower representation in the dataset demonstrate leading classification accuracy,the AMSA yields a 2.53%increase compared with state-of-the-art methods.
基金supported by the Wuhan University Undergraduate Project of Innovation and Entrepreneurship Training“The Evolution of Cartoon Images of Pandas in Western Media’s China-Related News From the Perspective of Multimodal Theory”(Project Number:S202410486013).
文摘Applying visual grammar theory,this study examines representational,interactive,and compositional meanings of the giant panda in Western media cartoons related to China from 1999 to the present.Distinct phases in the panda’s representation were identified and illustrated by cases of cartoons in major Western media.These phases trace shift of panda cartoon image from a symbol of peace and friendliness to a politicized emblem of China’s international stance.Key visual trends,such as transitivity,color symbolism,scale enlargement,and increasing compositional complexity,embody the panda’s role in shaping China’s global image and its function in international discourse.These trends reflect the panda’s transformation into a contested symbol,which mediates between China’s self-representation and Western perceptions of its geopolitical rise.By situating the analysis within the context of China’s growing global influence,this study contributes to visual and media studies,demonstrating how cultural symbols are recontextualized to reflect and shape geopolitical narratives.
基金Projects(50934002,51074013,51304076,51104100)supported by the National Natural Science Foundation of ChinaProject(IRT0950)supported by the Program for Changjiang Scholars Innovative Research Team in Universities,ChinaProject(2012M510007)supported by China Postdoctoral Science Foundation
文摘Methods and procedures of three-dimensional （3D） characterization of the pore structure features in the packed ore particle bed are focused. X-ray computed tomography was applied to deriving the cross-sectional images of specimens with single particle size of 1-2, 2-3, 3-4, 4-5, 5-6, 6-7, 7-8, 8-9, 9-10 ram. Based on the in-house developed 3D image analysis programs using Matlab, the volume porosity, pore size distribution and degree of connectivity were calculated and analyzed in detail. The results indicate that the volume porosity, the mean diameter of pores and the effective pore size （d50） increase with the increasing of particle size. Lognormal distribution or Gauss distribution is mostly suitable to model the pore size distribution. The degree of connectivity investigated on the basis of cluster-labeling algorithm also increases with increasing the particle size approximately.
文摘To develop a quick, accurate and antinoise automated image registration technique for infrared images, the wavelet analysis technique was used to extract the feature points in two images followed by the compensation for input image with angle difference between them. A hi erarchical feature matching algorithm was adopted to get the final transform parameters between the two images. The simulation results for two infrared images show that the method can effectively, quickly and accurately register images and be antinoise to some extent.
基金Supported by National Natural Science Foundation of China(No.82020108006,No.81730025).
文摘AIM:To summarize publication trends in the field of strabismus over the past 30y and predict future research hotspots.METHODS:A total of 2915 English-language articles and reviews on strabismus,published between 1993 and 2022,were retrieved from the Web of Science Core Collection.Bibliometric analyses were performed using VOSviewer and CiteSpace software to explore publication trends,as well as the contributions and collaborative networks of countries/regions,authors,institutions,and journals.RESULTS:The annual number of publications on strabismus showed a consistent upward trend.The United States(USA)maintained a leading position in this research field while Republic of Korea and China emerged as rapidly advancing contributors over the last decade.The University of California,Los Angeles ranked as the most productive institution,and Jonathan M.Holmes from USA was the most productive author.Journal of AAPOS was the leading journal with the most strabismus publications,whereas the two most highly cited articles were both published in Ophthalmology.Co-occurrence analysis identified pivotal keywords and burst terms,including intermittent exotropia(IXT),acute acquired comitant esotropia(AACE),functional magnetic resonance imaging(fMRI),and surgical treatment,which were confirmed as predominant and frontier topics.CONCLUSION:This study provides a comprehensive bibliometric analysis of strabismus research,revealing the evolution of research hotspots over the past 30y and outlining several cutting-edge directions for future investigation.
基金supports by the National Natural Science Foundation of China(Nos.82201135)"2015"Cultivation Program for Reserve Talents for Academic Leaders of Nanjing Stomatological School,Medical School of Nanjing University(No.0223A204).
文摘Early correction of childhood malocclusion is timely managing morphological,structural,and functional abnormalities at different dentomaxillofacial developmental stages.The selection of appropriate imaging examination and comprehensive radiological diagnosis and analysis play an important role in early correction of childhood malocclusion.This expert consensus is a collaborative effort by multidisciplinary experts in dentistry across the nation based on the current clinical evidence,aiming to provide general guidance on appropriate imaging examination selection,comprehensive and accurate imaging assessment for early orthodontic treatment patients.
文摘BACKGROUND Pancreatic cancer remains one of the most lethal malignancies worldwide,with a poor prognosis often attributed to late diagnosis.Understanding the correlation between pathological type and imaging features is crucial for early detection and appropriate treatment planning.AIM To retrospectively analyze the relationship between different pathological types of pancreatic cancer and their corresponding imaging features.METHODS We retrospectively analyzed the data of 500 patients diagnosed with pancreatic cancer between January 2010 and December 2020 at our institution.Pathological types were determined by histopathological examination of the surgical spe-cimens or biopsy samples.The imaging features were assessed using computed tomography,magnetic resonance imaging,and endoscopic ultrasound.Statistical analyses were performed to identify significant associations between pathological types and specific imaging characteristics.RESULTS There were 320(64%)cases of pancreatic ductal adenocarcinoma,75(15%)of intraductal papillary mucinous neoplasms,50(10%)of neuroendocrine tumors,and 55(11%)of other rare types.Distinct imaging features were identified in each pathological type.Pancreatic ductal adenocarcinoma typically presents as a hypodense mass with poorly defined borders on computed tomography,whereas intraductal papillary mucinous neoplasms present as characteristic cystic lesions with mural nodules.Neuroendocrine tumors often appear as hypervascular lesions in contrast-enhanced imaging.Statistical analysis revealed significant correlations between specific imaging features and pathological types(P<0.001).CONCLUSION This study demonstrated a strong association between the pathological types of pancreatic cancer and imaging features.These findings can enhance the accuracy of noninvasive diagnosis and guide personalized treatment approaches.
基金Supported by Research and Development Foundation for Major Science and Technology from Shenyang,No.19-112-4-105Big Data Foundation for Health Care from China Medical University,No.HMB201902105Natural Fund Guidance Plan from Liaoning,No.2019-ZD-0743.
文摘BACKGROUND It is evident that an accurate evaluation of T and N stage rectal cancer is essential for treatment planning.It has not been extensively investigated whether texture features derived from diffusion-weighted imaging(DWI)images and apparent diffusion coefficient(ADC)maps are associated with the extent of local invasion(pathological stage T1-2 vs T3-4)and nodal involvement(pathological stage N0 vs N1-2)in rectal cancer.AIM To predict different stages of rectal cancer using texture analysis based on DWI images and ADC maps.METHODS One hundred and fifteen patients with pathologically proven rectal cancer,who underwent preoperative magnetic resonance imaging,including DWI,were enrolled,retrospectively.The ADC measurements(ADCmean,ADCmin,ADCmax)as well as texture features,including the gray level co-occurrence matrix parameters,the gray level run-length matrix parameters and wavelet parameters were calculated based on DWI(b=0 and b=1000)images and the ADC maps.Independent sample t-tests or Mann-Whitney U tests were used for statistical analysis.Multivariate logistic regression analysis was conducted to establish the models.The predictive performance was validated by receiver operating characteristic curve analysis.RESULTS Dissimilarity,sum average,information correlation and run-length nonuniformity from DWIb=0 images,gray level nonuniformity,run percentage and run-length nonuniformity from DWIb=1000 images,and dissimilarity and run percentage from ADC maps were found to be independent predictors of local invasion(stage T3-4).The area under the operating characteristic curve of the model reached 0.793 with a sensitivity of 78.57%and a specificity of 74.19%.Sum average,gray level nonuniformity and the horizontal components of symlet transform(SymletH)from DWIb=0 images,sum average,information correlation,long run low gray level emphasis and SymletH from DWIb=1000 images,and ADCmax,ADCmean and information correlation from ADC maps were identified as independent predictors of nodal involvement.The area under the operating characteristic curve of the model reached 0.802 with a sensitivity of 80.77%and a specificity of 68.25%.CONCLUSION Texture features extracted from DWI images and ADC maps are useful clues for predicting pathological T and N stages in rectal cancer.
基金Supported by Interdisciplinary Program of Shanghai Jiao Tong University,No.YG2024 LC01National Natural Science Foundation of China,No.62406190.
文摘Confocal laser endomicroscopy(CLE)has become an indispensable tool in the diagnosis and detection of gastrointestinal(GI)diseases due to its high-resolution and high-contrast imaging capabilities.However,the early-stage imaging changes of gastrointestinal disorders are often subtle,and traditional medical image analysis methods rely heavily on manual interpretation,which is time-consuming,subject to observer variability,and inefficient for accurate lesion identification across large-scale image datasets.With the introduction of artificial intelligence(AI)technologies,AI-driven CLE image analysis systems can automatically extract pathological features and have demonstrated significant clinical value in lesion recognition,classification diagnosis,and malignancy prediction of GI diseases.These systems greatly enhance diagnostic efficiency and early detection capabilities.This review summarizes the applications of AI-assisted CLE in GI diseases,analyzes the limitations of current technologies,and explores future research directions.It is expected that the deep integration of AI and confocal imaging technologies will provide strong support for precision diagnosis and personalized treatment in the field of gastrointestinal disorders.
基金supported by National Natural Science Foundation of China(Nos.91220301,61175064 and 61273314)Postdoctoral Science Foundation of Central South University(No.126648)New Teacher Fund for School of Information Science and Engineering,Central South University(No.2012170301)
文摘We present two haze removal algorithms for single image based on haziness analysis.One algorithm regards haze as the veil layer,and the other takes haze as the transmission.The former uses the illumination component image obtained by retinex algorithm and the depth information of the original image to remove the veil layer.The latter employs guided filter to obtain the refined haze transmission and separates it from the original image.The main advantages of the proposed methods are that no user interaction is needed and the computing speed is relatively fast.A comparative study and quantitative evaluation with some main existing algorithms demonstrate that similar even better quality results can be obtained by the proposed methods.On the top of haze removal,several applications of the haze transmission including image refocusing,haze simulation,relighting and 2-dimensional(2D)to 3-dimensional(3D) stereoscopic conversion are also implemented.
文摘on the basis of analyzing the characteristics of low light level(LLL)image and ultra-violet image and the information amount of dual channel color night vision system,the LLL and ultra-violet color night vision technique is put forward.The methods of gray-scale modulation,frequency field fusion,special component fusion arc tried,and the improved LLL and ultra-violet image pseudo color fusion algorithms are presented.These new algorithms include subsection gray-scale modulation,image difference picking-up,component separation based on the reflected characteristics to night skylight reflection characteristics of objects and color space mapping which embodies the spectrum response of image sensor and nature vision.Some good results are obtained.
基金the National Natural Science Foundation of China (No. 19675005).
文摘Multi-modality medical image fusion has more and more important applications in medical image analysis and understanding. In this paper, we develop and apply a multi-resolution method based on wavelet pyramid to fuse medical images from different modalities such as PET-MRI and CT-MRI. In particular, we evaluate the different fusion results when applying different selection rules and obtain optimum combination of fusion parameters.
文摘Ultrasonic imaging logging provides continuous and oriented images of structures vs. depth. In the Chinese Continental Scientific Drilling (CCSD) Project, acoustic borehole images were recorded in the second pre-pilot drillhole which penetrates the metamorphic rocks. This paper focuses on fracture evaluation of the drillhole with these images. Both least square fit and a modified Hough transform are used for fracture extraction, and 269 fractures were mapped in the interval from 69.5 to 1 020 m. Most fractures dip steeply, with an average angle of 54°. Fracture dip directions are dominantly in the range of 220°-280° above the depth of 267 m, but 80°-120° in the lower zones. These observations may indicate the differences in structural movements or in-situ stress fields between the upper and lower zones in the drillhole.
文摘This paper delineates the images of Jiangxi Province as tourist destination perceived by about 2000 sample visitors at Lushan Mountain and other 3 famous resorts (Jinggangshan Mountains, Longhushan Mountain, and Sanqingshan Mountain), with a result that the most common image is the famous scenic mountain image with partial attribute of image of religious culture destination. In order to reveal the similarities and dissimilarities of images among the four destinations, a correspondence analysis on 16 image attributes was employed. The results indicate that the tourists’ images on Longhushan Mountain, Sanqingshan Mountain and Lushan Mountain are very similar: having a lot of good tourist sites, famous mountain scenery, being close to nature and having good guide service, and others, but religious culture and good shopping facilities having not made deep impression on tourist, while Jinggangshan Mountains is famous for its red culture. The correspondence analysis visualizes the strengths and weaknesses of the destinations, which is useful for market positioning among the competitive places. Finally, some marketing suggestions for the four destinations were provided.
文摘Wavelet-fractal based SAR （synthetic aperture radar） image processing is one of the advanced technologies in image processing. The main concept of analysis is that after wavelet transformation, multifractal spectrum of the signal is different from that of noise. This difference is used to alleviate the noise produced by SAR image.The method to denoise SAR image using the process based on wavelet-fractai analysis is discussed in detail. Essentially, the present method focuses on adjusting the Hoelder exponent α of multifractal spectrum. After simulation, α should be adjusted to 1.72-1.73. The more the value of α exceeds 1.73, the less distinctive the edges of SAR image become. According to the authors denoising is optimal at α=1.72-1.73. In other words, when α =1.72-1.73, a smooth and denoised SAR image is produced.
文摘The aim of the present study was to compare assessments of sperm concentration and sperm motility analysed by conventional semen analysis with those obtained by computer-assisted semen analysis （CASA） （Copenhagen Rigshospitalet Image House Sperm Motility Analysis System （CRISMAS） 4.6 software） using semen samples from 166 young Danish men. The CRISMAS software identifies sperm concentration and classifies spermatozoa into three motility categories. To enable comparison of the two methods, the four motility stages obtained by conventional semen analysis were, based on their velocity classifications, divided into three stages, comparable to the three CRISMAS motility categories： rapidly progressive （A）, slowly progressive （B） and non-progressive （C＋ D）. Differences between the two methods were large for all investigated parameters （P〈0.001）. CRISMAS overestimated sperm concentration and the proportion of rapidly progressive spermatozoa and, consequently, underestimated the percentages of slowly progressive and non-progressive spermatozoa, compared to the conventional method. To investigate whether results drifted according to time of semen analysis, results were pooled into quarters according to date of semen analysis. CRISMAS motility results appeared more stable over time compared to the conventional analysis; however, neither method showed any trends. Apparently, CRISMAS CASA results and results from the conventional method were not comparable with respect to sperm concentration and motility analysis. This needs to be accounted for in clinics using this software and in studies of determinants of these semen characteristics.
基金Supported by the NationalNaturalScience Foundation of China( No. 2 0 175 0 1) and U niversity Key Teachers Programdirected under the Ministry of Education ofP.R.China( No. 2 0 0 0 - 6 5 )
文摘It is critical to establish a direct and precise method with a high sensitivity and selectivity in analytical chemistry. In this research, making use of a well known phenomenon of capillary flow, we have proposed an image analysis method of nucleic acids at the price of a small amount of sample. When a droplet of the supramolecular complex solution, formed by neutral red and nucleic acids(NA) under an approximate neutral condition, was placed on the hydrophobic surface of dimethyl dichlorosilane pretreated glass slides, and it was evaporated, the supramolecular complex exhibited the periphery of the droplet due to the capillary effect, and accumulated there to form a red capillary flow directed assembly ring(CFDAR). A typical CFDAR has an outer diameter of (2 r ) about 1.18 mm and a ring width(2 δ ) of about 41 μm. Depending on the experimental conditions, a variety of CFDAR can be assembled. The experimental results are in agreement with our former theoretical discussion. It was found that when a droplet volume is 0.1 μL, the fluorescence intensity of the CFDAR formed by the NR NA is in proportion to the content of calf thymus DNA in the range of 0-0.28 ng, fish sperm DNA of 0-0.24 ng and yeast RNA of 0-0.16 ng with the limit of detection(3 σ ) of 1 7, 1.4 and 0.9 pg, respectively for the three nucleic acids.
