期刊文献+
共找到346篇文章
< 1 2 18 >
每页显示 20 50 100
Pulmonary Edema and Pleural Effusion Detection Using Efficient Net-V1-B4 Architecture and AdamW Optimizer from Chest X-Rays Images
1
作者 Anas AbuKaraki Tawfi Alrawashdeh +4 位作者 Sumaya Abusaleh Malek Zakarya Alksasbeh Bilal Alqudah Khalid Alemerien Hamzah Alshamaseen 《Computers, Materials & Continua》 SCIE EI 2024年第7期1055-1073,共19页
This paper presents a novelmulticlass systemdesigned to detect pleural effusion and pulmonary edema on chest Xray images,addressing the critical need for early detection in healthcare.A new comprehensive dataset was f... This paper presents a novelmulticlass systemdesigned to detect pleural effusion and pulmonary edema on chest Xray images,addressing the critical need for early detection in healthcare.A new comprehensive dataset was formed by combining 28,309 samples from the ChestX-ray14,PadChest,and CheXpert databases,with 10,287,6022,and 12,000 samples representing Pleural Effusion,Pulmonary Edema,and Normal cases,respectively.Consequently,the preprocessing step involves applying the Contrast Limited Adaptive Histogram Equalization(CLAHE)method to boost the local contrast of the X-ray samples,then resizing the images to 380×380 dimensions,followed by using the data augmentation technique.The classification task employs a deep learning model based on the EfficientNet-V1-B4 architecture and is trained using the AdamW optimizer.The proposed multiclass system achieved an accuracy(ACC)of 98.3%,recall of 98.3%,precision of 98.7%,and F1-score of 98.7%.Moreover,the robustness of the model was revealed by the Receiver Operating Characteristic(ROC)analysis,which demonstrated an Area Under the Curve(AUC)of 1.00 for edema and normal cases and 0.99 for effusion.The experimental results demonstrate the superiority of the proposedmulti-class system,which has the potential to assist clinicians in timely and accurate diagnosis,leading to improved patient outcomes.Notably,ablation-CAM visualization at the last convolutional layer portrayed further enhanced diagnostic capabilities with heat maps on X-ray images,which will aid clinicians in interpreting and localizing abnormalities more effectively. 展开更多
关键词 Image classification decision support system EfficientNet-V1-B4 AdamW optimizer pulmonary edema pleural effusion chest x-rays
下载PDF
Metal-Halide Perovskite Submicrometer-Thick Films for Ultra-Stable Self-Powered Direct X-Ray Detectors
2
作者 Marco Girolami Fabio Matteocci +7 位作者 Sara Pettinato Valerio Serpente Eleonora Bolli Barbara Paci Amanda Generosi Stefano Salvatori Aldo Di Carlo Daniele M.Trucchi 《Nano-Micro Letters》 SCIE EI CAS CSCD 2024年第9期410-431,共22页
Metal-halide perovskites are revolutionizing the world of X-ray detectors,due to the development of sensitive,fast,and cost-effective devices.Self-powered operation,ensuring portability and low power consumption,has a... Metal-halide perovskites are revolutionizing the world of X-ray detectors,due to the development of sensitive,fast,and cost-effective devices.Self-powered operation,ensuring portability and low power consumption,has also been recently demonstrated in both bulk materials and thin films.However,the signal stability and repeatability under continuous X-ray exposure has only been tested up to a few hours,often reporting degradation of the detection performance.Here it is shown that self-powered direct X-ray detectors,fabricated starting from a FAPbBr_(3)submicrometer-thick film deposition onto a mesoporous TiO_(2)scaffold,can withstand a 26-day uninterrupted X-ray exposure with negligible signal loss,demonstrating ultra-high operational stability and excellent repeatability.No structural modification is observed after irradiation with a total ionizing dose of almost 200 Gy,revealing an unexpectedly high radiation hardness for a metal-halide perovskite thin film.In addition,trap-assisted photoconductive gain enabled the device to achieve a record bulk sensitivity of 7.28 C Gy^(−1)cm^(−3)at 0 V,an unprecedented value in the field of thin-film-based photoconductors and photodiodes for“hard”X-rays.Finally,prototypal validation under the X-ray beam produced by a medical linear accelerator for cancer treatment is also introduced. 展开更多
关键词 Metal-halide perovskite thin films Direct x-ray detectors Self-powered devices Operational stability Medical linear accelerator
下载PDF
Centimeter-sized Cs_(3)Cu_(2)I_(5)single crystals grown by oleic acid assisted inverse temperature crystallization strategy and their films for high-quality X-ray imaging 被引量:1
3
作者 Tao Chen Xin Li +9 位作者 Yong Wang Feng Lin Ruliang Liu Wenhua Zhang Jie Yang Rongfei Wang Xiaoming Wen Bin Meng Xuhui Xu Chong Wang 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2023年第4期382-389,共8页
Low-dimensional halide perovskites have become the most promising candidates for X-ray imaging,yet the issues of the poor chemical stability of hybrid halide perovskite,the high poisonousness of lead halides and the r... Low-dimensional halide perovskites have become the most promising candidates for X-ray imaging,yet the issues of the poor chemical stability of hybrid halide perovskite,the high poisonousness of lead halides and the relatively low detectivity of the lead-free halide perovskites which seriously restrain its commercialization.Here,we developed a solution inverse temperature crystal growth(ITCG)method to bring-up high quality Cs_(3)Cu_(2)I_(5)crystals with large size of centimeter order,in which the oleic acid(OA)is introduced as an antioxidative ligand to inhibit the oxidation of cuprous ions effieiently,as well as to decelerate the crystallization rate remarkalby.Based on these fine crystals,the vapor deposition technique is empolyed to prepare high quality Cs_(3)Cu_(2)I_(5)films for efficient X-ray imaging.Smooth surface morphology,high light yields and short decay time endow the Cs_(3)Cu_(2)I_(5)films with strong radioluminescence,high resolution(12 lp/mm),low detection limits(53 nGyair/s)and desirable stability.Subsequently,the Cs_(3)Cu_(2)I_(5)films have been applied to the practical radiography which exhibit superior X-ray imaging performance.Our work provides a paradigm to fabricate nonpoisonous and chemically stable inorganic halide perovskite for X-ray imaging. 展开更多
关键词 Inverse temperature crystal growth Cs_(3)Cu_(2)I_(5)single crystal Vapor deposition Cs_(3)Cu_(2)I_(5)films x-ray imaging
下载PDF
Optimal Synergic Deep Learning for COVID-19 Classification Using Chest X-Ray Images
4
作者 JoséEscorcia-Gutierrez Margarita Gamarra +3 位作者 Roosvel Soto-Diaz Safa Alsafari Ayman Yafoz Romany F.Mansour 《Computers, Materials & Continua》 SCIE EI 2023年第6期5255-5270,共16页
A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the lungs.Chest X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imagin... A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the lungs.Chest X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and portability.In radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer variability.Using lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is advantageous.The current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on optimization.The data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s edges.Then,the OSDL model is applied to classify the CXRs under different severity levels based on CXR data.The learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the work.OSDL model,applied in this study,was validated using the COVID-19 dataset.The experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%. 展开更多
关键词 Artificial intelligence chest x-ray COVID-19 optimized synergic deep learning PREPROCESSING public health
下载PDF
Histogram Matched Chest X-Rays Based Tuberculosis Detection Using CNN
5
作者 Joe Louis Paul Ignatius Sasirekha Selvakumar +3 位作者 Kavin Gabriel Joe Louis Paul Aadhithya B.Kailash S.Keertivaas S.A.J.Akarvin Raja Prajan 《Computer Systems Science & Engineering》 SCIE EI 2023年第1期81-97,共17页
Tuberculosis(TB)is a severe infection that mostly affects the lungs and kills millions of people’s lives every year.Tuberculosis can be diagnosed using chest X-rays(CXR)and data-driven deep learning(DL)approaches.Bec... Tuberculosis(TB)is a severe infection that mostly affects the lungs and kills millions of people’s lives every year.Tuberculosis can be diagnosed using chest X-rays(CXR)and data-driven deep learning(DL)approaches.Because of its better automated feature extraction capability,convolutional neural net-works(CNNs)trained on natural images are particularly effective in image cate-gorization.A combination of 3001 normal and 3001 TB CXR images was gathered for this study from different accessible public datasets.Ten different deep CNNs(Resnet50,Resnet101,Resnet152,InceptionV3,VGG16,VGG19,DenseNet121,DenseNet169,DenseNet201,MobileNet)are trained and tested for identifying TB and normal cases.This study presents a deep CNN approach based on histogram matched CXR images that does not require object segmenta-tion of interest,and this coupled methodology of histogram matching with the CXRs improves the accuracy and detection performance of CNN models for TB detection.Furthermore,this research contains two separate experiments that used CXR images with and without histogram matching to classify TB and non-TB CXRs using deep CNNs.It was able to accurately detect TB from CXR images using pre-processing,data augmentation,and deep CNN models.Without histogram matching the best accuracy,sensitivity,specificity,precision and F1-score in the detection of TB using CXR images among ten models are 99.25%,99.48%,99.52%,99.48%and 99.22%respectively.With histogram matching the best accuracy,sensitivity,specificity,precision and F1-score are 99.58%,99.82%,99.67%,99.65%and 99.56%respectively.The proposed meth-odology,which has cutting-edge performance,will be useful in computer-assisted TB diagnosis and aids in minimizing irregularities in TB detection in developing countries. 展开更多
关键词 Tuberculosis detection chest x-ray(CXR) convolutional neural networks(CNNs) transfer learning histogram matching
下载PDF
COVID-19 Detection from Chest X-Ray Images Using Convolutional Neural Network Approach
6
作者 Md. Harun Or Rashid Muzakkir Hossain Minhaz +2 位作者 Ananya Sarker Must. Asma Yasmin Md. Golam An Nihal 《Journal of Computer and Communications》 2023年第5期29-41,共13页
COVID-19 is a respiratory illness caused by the SARS-CoV-2 virus, first identified in 2019. The primary mode of transmission is through respiratory droplets when an infected person coughs or sneezes. Symptoms can rang... COVID-19 is a respiratory illness caused by the SARS-CoV-2 virus, first identified in 2019. The primary mode of transmission is through respiratory droplets when an infected person coughs or sneezes. Symptoms can range from mild to severe, and timely diagnosis is crucial for effective treatment. Chest X-Ray imaging is one diagnostic tool used for COVID-19, and a Convolutional Neural Network (CNN) is a popular technique for image classification. In this study, we proposed a CNN-based approach for detecting COVID-19 in chest X-Ray images. The model was trained on a dataset containing both COVID-19 positive and negative cases and evaluated on a separate test dataset to measure its accuracy. Our results indicated that the CNN approach could accurately detect COVID-19 in chest X-Ray images, with an overall accuracy of 97%. This approach could potentially serve as an early diagnostic tool to reduce the spread of the virus. 展开更多
关键词 COVID-19 chest x-ray Images CNN VIRUS ACCURACY
下载PDF
High Energy X-Ray Dosimetry Using(ZnO)_(0.2)(TeO_(2))_(0.8)Thin Film-based Real-time X-Ray Sensor
7
作者 M.M.Idris I.O.Olarinoye +2 位作者 M.T.Kolo S.O.Ibrahim J.K.Audu 《Non-Metallic Material Science》 2023年第1期4-13,共10页
This study reports the dosimetric response of a(ZnO)_(0.2)(TeO_(2))_(0.8)thin film sensor irradiated with high-energy X-ray radiation at various doses.The spray pyrolysis method was used for the film deposition on sod... This study reports the dosimetric response of a(ZnO)_(0.2)(TeO_(2))_(0.8)thin film sensor irradiated with high-energy X-ray radiation at various doses.The spray pyrolysis method was used for the film deposition on soda-lime glass substrate using zinc acetate dehydrate and tellurium dioxide powder as the starting precursors.The structural and morphological properties of the film were determined.The I-V characteristics measurements were performed during irradiation with a 6 MV X-ray beam from a Linac.The results revealed that the XRD pattern of the AS-deposited thin film is non-crystalline(amorphous)in nature.The FESEM image shows the non-uniform shape of nanoparticles agglomerated separately,and the EDX spectrum shows the presence of Te,Zn,and O in the film.The I-V characteristics measurements indicate that the current density increases linearly with X-ray doses(0-250 cGy)for all applied voltages(1-6 V).The sensitivity of the thin film sensor has been found to be in the range of 0.37-0.94 mA/cm^(2)/Gy.The current-voltage measurement test for fading normalised in percentage to day 0 was found in the order of day 0>day 15>day 30>day 1>day 2.These results are expected to be beneficial for fabricating cheap and practical X-ray sensors. 展开更多
关键词 Thin film x-ray radiation I-V characteristics DOSIMETRY
下载PDF
Dual-phase coexistence enables to alleviate resistance drift in phase-change films
8
作者 Tong Wu Chen Chen +2 位作者 Jinyi Zhu Guoxiang Wang Shixun Dai 《Journal of Semiconductors》 EI CAS CSCD 2024年第7期55-59,共5页
The amorphous phase-change materials with spontaneous structural relaxation leads to the resistance drift with the time for phase-change neuron synaptic devices. Here, we modify the phase change properties of the conv... The amorphous phase-change materials with spontaneous structural relaxation leads to the resistance drift with the time for phase-change neuron synaptic devices. Here, we modify the phase change properties of the conventional Ge_2Sb_2Te_5(GST) material by introducing an SnS phase. It is found that the resistance drift coefficient of SnS-doped GST was decreased from 0.06 to 0.01. It can be proposed that the origin originates from the precipitation of GST nanocrystals accompanied by the precipitation of SnS crystals compared to single-phase GST compound systems. We also found that the decrease in resistance drift can be attributed to the narrowed bandgap from 0.65 to 0.43 eV after SnS-doping. Thus, this study reveals the quantitative relationship between the resistance drift and the band gap and proposes a new idea for alleviating the resistance drift by composition optimization, which is of great significance for finding a promising phase change material. 展开更多
关键词 phase change films x-ray methods resistance drift optical band gap
下载PDF
Relationship between neonatal respiratory distress syndrome pulmonary ultrasonography and respiratory distress score,oxygenation index,and chest radiography grading
9
作者 Hai Yang Li-Jun Gao +5 位作者 Jing Lei Qiang Li Liu Cui Xiao-Hua Li Wu-Xuan Yin Sen-Hua Tian 《World Journal of Clinical Cases》 SCIE 2024年第20期4154-4165,共12页
BACKGROUND Accurate condition assessment is critical for improving the prognosis of neonatal respiratory distress syndrome(RDS),but current assessment methods for RDS pose a cumulative risk of harm to neonates.Thus,a ... BACKGROUND Accurate condition assessment is critical for improving the prognosis of neonatal respiratory distress syndrome(RDS),but current assessment methods for RDS pose a cumulative risk of harm to neonates.Thus,a less harmful method for assessing the health of neonates with RDS is needed.AIM To analyze the relationships between pulmonary ultrasonography and respiratory distress scores,oxygenation index,and chest X-ray grade of neonatal RDS to identify predictors of neonatal RDS severity.METHODS This retrospective study analyzed the medical information of 73 neonates with RDS admitted to the neonatal intensive care unit of Liupanshui Maternal and Child Care Service Center between April and December 2022.The pulmonary ultrasonography score,respiratory distress score,oxygenation index,and chest Xray grade of each newborn before and after treatment were collected.Spearman correlation analysis was performed to determine the relationships among these values and neonatal RDS severity.RESULTS The pulmonary ultrasonography score,respiratory distress score,oxygenation index,and chest X-ray RDS grade of the neonates were significantly lower after treatment than before treatment(P<0.05).Spearman correlation analysis showed that before and after treatment,the pulmonary ultrasonography score of neonates with RDS was positively correlated with the respiratory distress score,oxygenation index,and chest X-ray grade(ρ=0.429–0.859,P<0.05).Receiver operating characteristic curve analysis indicated that pulmonary ultrasonography screening effectively predicted the severity of neonatal RDS(area under the curve=0.805–1.000,P<0.05).CONCLUSION The pulmonary ultrasonography score was significantly associated with the neonatal RDS score,oxygenation index,and chest X-ray grade.The pulmonary ultrasonography score was an effective predictor of neonatal RDS severity. 展开更多
关键词 Neonatal respiratory distress syndrome Pulmonary ultrasonography Ultrasonography score Respiratory distress score Oxygenation index chest x-ray grading
下载PDF
Tuberculosis Diagnosis and Visualization with a Large Vietnamese X-Ray Image Dataset
10
作者 Nguyen Trong Vinh Lam Thanh Hien +2 位作者 Ha Manh Toan Ngo Duc Vinh Do Nang Toan 《Intelligent Automation & Soft Computing》 2024年第2期281-299,共19页
Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse it.Significantly,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very difficult.The la... Tuberculosis is a dangerous disease to human life,and we need a lot of attempts to stop and reverse it.Significantly,in theCOVID-19 pandemic,access to medical services for tuberculosis has become very difficult.The late detection of tuberculosis could lead to danger to patient health,even death.Vietnamis one of the countries heavily affected by the COVID-19 pandemic,andmany residential areas as well as hospitals have to be isolated for a long time.Reality demands a fast and effective tuberculosis diagnosis solution to deal with the difficulty of accessingmedical services,such as an automatic tuberculosis diagnosis system.In our study,aiming to build that system,we were interested in the tuberculosis diagnosis problem from the chest X-ray images of Vietnamese patients.The chest X-ray image is an important data type to diagnose tuberculosis,and it has also received a lot of attention from deep learning researchers.This paper proposed a novel method for tuberculosis diagnosis and visualization using the deeplearning approach with a large Vietnamese X-ray image dataset.In detail,we designed our custom convolutional neural network for the X-ray image classification task and then analyzed the predicted result to provide visualization as a heat-map.To prove the performance of our network model,we conducted several experiments to compare it to another study and also to evaluate it with the dataset of this research.To support the implementation,we built a specific annotation system for tuberculosis under the requirements of radiologists in the Vietnam National Lung Hospital.A large experiment dataset was also from this hospital,and most of this data was for training the convolutional neural network model.The experiment results were evaluated regarding sensitivity,specificity,and accuracy.We achieved high scores with a training accuracy score of 0.99,and the testing specificity and sensitivity scores were over 0.9.Based on the X-ray image classification result,we visualize prediction results as heat-maps and also analyze them in comparison with annotated symptoms of radiologists. 展开更多
关键词 Tuberculosis classification Vietnamese chest x-ray deep learning
下载PDF
Transfer Learning Approach to Classify the X-Ray Image that Corresponds to Corona Disease Using ResNet50 Pre-Trained by ChexNet
11
作者 Mahyar Bolhassani 《Journal of Intelligent Learning Systems and Applications》 2024年第2期80-90,共11页
The COVID-19 pandemic has had a widespread negative impact globally. It shares symptoms with other respiratory illnesses such as pneumonia and influenza, making rapid and accurate diagnosis essential to treat individu... The COVID-19 pandemic has had a widespread negative impact globally. It shares symptoms with other respiratory illnesses such as pneumonia and influenza, making rapid and accurate diagnosis essential to treat individuals and halt further transmission. X-ray imaging of the lungs is one of the most reliable diagnostic tools. Utilizing deep learning, we can train models to recognize the signs of infection, thus aiding in the identification of COVID-19 cases. For our project, we developed a deep learning model utilizing the ResNet50 architecture, pre-trained with ImageNet and CheXNet datasets. We tackled the challenge of an imbalanced dataset, the CoronaHack Chest X-Ray dataset provided by Kaggle, through both binary and multi-class classification approaches. Additionally, we evaluated the performance impact of using Focal loss versus Cross-entropy loss in our model. 展开更多
关键词 x-ray Classification Convolutional Neural Network ResNet Transfer Learning Supervised Learning COVID-19 chest x-ray
下载PDF
Chest Radiography: General Practitioners’ Compliance with Recommendations
12
作者 Milckisédek Judicaël Marouruana Some Aïda Ida Tankoano +3 位作者 Pakisba Ali Ouedraogo Bassirou Kindo Nina-Astrid Ouedraogo Mohammed Ali Harchaoui 《Open Journal of Medical Imaging》 2024年第2期56-63,共8页
Introduction: Chest radiography is the most frequently prescribed imaging test in general practice in France. We aimed to assess the extent to which general practitioners follow the recommendations of the French Natio... Introduction: Chest radiography is the most frequently prescribed imaging test in general practice in France. We aimed to assess the extent to which general practitioners follow the recommendations of the French National Authority for Health in prescribing chest radiography. Methodology: We conducted a retrospective analysis study, in two radiology centers belonging to the same group in Saint-Omer and Aire-sur-la-Lys, of requests for chest radiography sent by general practitioners over the winter period between December 22, 2013, and March 21, 2014, for patients aged over 18 years. Results: One hundred and seventy-seven requests for chest X-rays were analyzed, 71.75% of which complied with recommendations. The most frequent reason was the search for bronchopulmonary infection, accounting for 70.08% of prescriptions, followed by 11.2% for requests to rule out pulmonary neoplasia, whereas the latter reason did not comply with recommendations. Chest X-rays contributed to a positive diagnosis in 28.81% of cases. The positive diagnosis was given by 36.22% of the recommended chest X-rays, versus 10% for those not recommended. Conclusion: In most cases, general practitioners follow HAS recommendations for prescribing chest X-rays. Non-recommended chest X-rays do not appear to make a major contribution to diagnosis or patient management, confirming the value of following the recommendations of the French National Authority for Health. 展开更多
关键词 chest x-ray RECOMMENDATIONS General Practitioners PRESCRIPTION
下载PDF
Evaluation on residual stresses of silicon-doped CVD diamond films using X-ray diffraction and Raman spectroscopy 被引量:10
13
作者 陈苏琳 沈彬 +2 位作者 张建国 王亮 孙方宏 《Transactions of Nonferrous Metals Society of China》 SCIE EI CAS CSCD 2012年第12期3021-3026,共6页
The effect of silicon doping on the residual stress of CVD diamond films is examined using both X-ray diffraction (XRD) analysis and Raman spectroscopy measurements. The examined Si-doped diamond films are deposited o... The effect of silicon doping on the residual stress of CVD diamond films is examined using both X-ray diffraction (XRD) analysis and Raman spectroscopy measurements. The examined Si-doped diamond films are deposited on WC-Co substrates in a home-made bias-enhanced HFCVD apparatus. Ethyl silicate (Si(OC2H5)4) is dissolved in acetone to obtain various Si/C mole ratio ranging from 0.1% to 1.4% in the reaction gas. Characterizations with SEM and XRD indicate increasing silicon concentration may result in grain size decreasing and diamond [110] texture becoming dominant. The residual stress values of as-deposited Si-doped diamond films are evaluated by both sin2ψ method, which measures the (220) diamond Bragg diffraction peaks using XRD, with ψ-values ranging from 0° to 45°, and Raman spectroscopy, which detects the diamond Raman peak shift from the natural diamond line at 1332 cm-1. The residual stress evolution on the silicon doping level estimated from the above two methods presents rather good agreements, exhibiting that all deposited Si-doped diamond films present compressive stress and the sample with Si/C mole ratio of 0.1% possesses the largest residual stress of ~1.75 GPa (Raman) or ~2.3 GPa (XRD). As the silicon doping level is up further, the residual stress reduces to a relative stable value around 1.3 GPa. 展开更多
关键词 silicon-doped diamond films silicon doping residual stress x-ray diffraction Raman spectroscopy
下载PDF
Covid-19 Detection from Chest X-Ray Images Using Advanced Deep Learning Techniques 被引量:3
14
作者 Shubham Mahajan Akshay Raina +2 位作者 Mohamed Abouhawwash Xiao-Zhi Gao Amit Kant Pandit 《Computers, Materials & Continua》 SCIE EI 2022年第1期1541-1556,共16页
Like the Covid-19 pandemic,smallpox virus infection broke out in the last century,wherein 500 million deaths were reported along with enormous economic loss.But unlike smallpox,the Covid-19 recorded a low exponential ... Like the Covid-19 pandemic,smallpox virus infection broke out in the last century,wherein 500 million deaths were reported along with enormous economic loss.But unlike smallpox,the Covid-19 recorded a low exponential infection rate and mortality rate due to advancement inmedical aid and diagnostics.Data analytics,machine learning,and automation techniques can help in early diagnostics and supporting treatments of many reported patients.This paper proposes a robust and efficient methodology for the early detection of COVID-19 from Chest X-Ray scans utilizing enhanced deep learning techniques.Our study suggests that using the Prediction and Deconvolutional Modules in combination with the SSD architecture can improve the performance of the model trained at this task.We used a publicly open CXR image dataset and implemented the detectionmodelwith task-specific pre-processing and near 80:20 split.This achieved a competitive specificity of 0.9474 and a sensibility/accuracy of 0.9597,which shall help better decision-making for various aspects of identification and treat the infection. 展开更多
关键词 Machine learning deep learning object detection chest x-ray medical images Covid-19
下载PDF
Automatic Detection of COVID-19 Using Chest X-Ray Images and Modified ResNet18-Based Convolution Neural Networks 被引量:3
15
作者 Ruaa A.Al-Falluji Zainab Dalaf Katheeth Bashar Alathari 《Computers, Materials & Continua》 SCIE EI 2021年第2期1301-1313,共13页
The latest studies with radiological imaging techniques indicate that X-ray images provide valuable details on the Coronavirus disease 2019(COVID-19).The usage of sophisticated artificial intelligence technology(AI)an... The latest studies with radiological imaging techniques indicate that X-ray images provide valuable details on the Coronavirus disease 2019(COVID-19).The usage of sophisticated artificial intelligence technology(AI)and the radiological images can help in diagnosing the disease reliably and addressing the problem of the shortage of trained doctors in remote villages.In this research,the automated diagnosis of Coronavirus disease was performed using a dataset of X-ray images of patients with severe bacterial pneumonia,reported COVID-19 disease,and normal cases.The goal of the study is to analyze the achievements for medical image recognition of state-of-the-art neural networking architectures.Transfer Learning technique has been implemented in this work.Transfer learning is an ambitious task,but it results in impressive outcomes for identifying distinct patterns in tiny datasets of medical images.The findings indicate that deep learning with X-ray imagery could retrieve important biomarkers relevant for COVID-19 disease detection.Since all diagnostic measures show failure levels that pose questions,the scientific profession should determine the probability of integration of X-rays with the clinical treatment,utilizing the results.The proposed model achieved 96.73%accuracy outperforming the ResNet50 and traditional Resnet18 models.Based on our findings,the proposed system can help the specialist doctors in making verdicts for COVID-19 detection. 展开更多
关键词 COVID-19 artificial intelligence convolutional neural network chest x-ray images Resnet18 model
下载PDF
Diagnostic Value of the Thoracic Ultrasonography Compared to Conventional Chest X-Rays in Pneumonia for Children between 0 to 15 Years: Case Study in Two Hospitals in Yaoundé 被引量:2
16
作者 Seme Engoumou Ambroise Merci Mbede Maggy +3 位作者 Awana Armel Philippe Bilounga Ndengue Priscille Edith Onguene Julienne Zeh Odile Fernande 《Open Journal of Radiology》 2019年第1期10-19,共10页
Introduction: The diagnosis of pneumonia is usually made based on clinical manifestations and chest X-ray. The use of ultrasound in detecting pulmonary diseases in general, and especially consolidation syndrome has be... Introduction: The diagnosis of pneumonia is usually made based on clinical manifestations and chest X-ray. The use of ultrasound in detecting pulmonary diseases in general, and especially consolidation syndrome has been demonstrated. The objective of this study was to determine the accuracy of thoracic ultrasound compared to chest X-ray in the diagnosis of infectious pneumonia in children. Methods: Children between 0 to 15 years were included in our study. The lung ultrasound results obtained were compared with those of the chest X-ray used as the reference. Our data were introduced into the EpiInfo 3.5.4 software and analyzed with the EpiInfo 3.5.4 and IBMSPSS Statistics version 20.0 softwares. Microsoft Office Excel 2016 was used to produce Charts. Continuous quantitative variables were presented. Cohen’s Kappa concordance test was applied with confidence interval of 95%. Results: 52 children were enrolled in the study. In imaging, the dominant sign was consolidation syndrome (75.0%) of cases by chest radiography, and in 78.8% of cases by lung ultrasound (p Conclusion: Our study demonstrated that lung echography is a non-ionizing and reliable tool in the diagnosis of childhood’s pneumonia. 展开更多
关键词 LUNG Ultrasound chest x-ray PNEUMONIA CHILDREN Yaoundé Cameroon
下载PDF
X-ray absorption near the edge structure and x-ray photoelectron spectroscopy studies on pyrite prepared by thermally sulfurizing iron films 被引量:1
17
作者 张辉 刘应书 +3 位作者 王宝义 魏龙 奎热西 钱海杰 《Chinese Physics B》 SCIE EI CAS CSCD 2009年第7期2734-2738,共5页
This paper reports how pyrite films were prepared by thermal sulfurization of magnetron sputtered iron films and characterized by X-ray absorption near edge structure spectra and X-ray photoelectron spectroscopy on a ... This paper reports how pyrite films were prepared by thermal sulfurization of magnetron sputtered iron films and characterized by X-ray absorption near edge structure spectra and X-ray photoelectron spectroscopy on a 4B9B beam line at the Beijing Synchrotron Radiation Facility. The band gap of the pyrite agrees well with the optical band gap obtained by a spectrophotometer. The octahedral symmetry of pyrite leads to the splitting of the d orbit into t2g and eg levels. The high spin and low spin states were analysed through the difference of electron exchange interaction and the orbital crystal field. Only when the crystal field splitting is higher than 1.5 eV, the two weak peaks above the white lines can appear, and this was approved by experiments in the present work. 展开更多
关键词 x-ray absorption near the edge structure spectra x-ray photoelectron spectroscopy iron pyrite films solar cells
下载PDF
X-ray Photoelectron Spectroscopy Studies of Ti_(x)Al_(1-x)N Thin Films Prepared by RF Reactive Magnetron Sputtering 被引量:1
18
作者 Rui XIONG Jing SHI 《Journal of Materials Science & Technology》 SCIE EI CAS CSCD 2005年第4期541-544,共4页
TixAl1-xN films have been prepared by RF reactive magnetron sputtering. X-ray diffraction results showed that TixAl1-xN thin films in this study were hexagonal wurtzite structure with the Ti content up to 0.18. X-ray ... TixAl1-xN films have been prepared by RF reactive magnetron sputtering. X-ray diffraction results showed that TixAl1-xN thin films in this study were hexagonal wurtzite structure with the Ti content up to 0.18. X-ray photoelectron spectrocopy studies provided that the Nls core-electron spectrum of TixAl1-xN thin film brodend with increasing Ti content, and the difference of the chemical shifts for Ti2p3/2 line between TiN and TixAl1-xN th77pj in film was 0.7 eV. 展开更多
关键词 TixAl1-xN films x-ray photoelectron spectroscopy Core-electron spectrum
下载PDF
A large-grain-size thick-film polycrystalline diamond detector for x-ray detection 被引量:1
19
作者 Ping XU Yi YU +1 位作者 Haiyang ZHOU Changjun QIU 《Plasma Science and Technology》 SCIE EI CAS CSCD 2020年第12期97-103,共7页
A diamond film with a size of 6×6×0.5 mm^3 is fabricated by electron-assisted chemical vapor deposition. Raman spectrum analysis, x-ray diffraction and scanning electron microscope images confirm the high pu... A diamond film with a size of 6×6×0.5 mm^3 is fabricated by electron-assisted chemical vapor deposition. Raman spectrum analysis, x-ray diffraction and scanning electron microscope images confirm the high purity and large grain size, which is larger than 300 μm. Its resistivity is higher than 10^12 W· cm. Interlaced-finger electrodes are imprinted onto the diamond film to develop an x-ray detector. Ohmic contact is confirmed by checking the linearity of its current–voltage curve. The dark current is lower than 0.1 n A under an electric field of 30 k V cm^-1. The time response is 220 ps. The sensitivity is about 125 m A W^-1 under a biasing voltage of 100 V.A good linear radiation dose rate is also confirmed. This diamond detector is used to measure x-ray on a Z-pinch, which has a double-layer 'nested tungsten wire array'. The pronounced peaks in the measured waveform clearly characterize the x-ray bursts, which proves the performance of this diamond detector. 展开更多
关键词 polycrystalline diamond film x-ray detector electron-assisted chemical vapor deposition
下载PDF
Characterization of Thin Films by Low Incidence X-Ray Diffraction 被引量:2
20
作者 Mirtat Bouroushian Tatjana Kosanovic 《Crystal Structure Theory and Applications》 2012年第3期35-39,共5页
Glancing Angle X-ray Diffraction (GAXRD) is introduced as a direct, non-destructive, surface-sensitive technique for analysis of thin films. The method was applied to polycrystalline thin films (namely, titanium oxide... Glancing Angle X-ray Diffraction (GAXRD) is introduced as a direct, non-destructive, surface-sensitive technique for analysis of thin films. The method was applied to polycrystalline thin films (namely, titanium oxide, zinc selenide, cadmium selenide and combinations thereof) obtained by electrochemical growth, in order to determine the composition of ultra-thin surface layers, to estimate film thickness, and perform depth profiling of multilayered heterostructures. The experimental data are treated on the basis of a simple absorption-diffraction model involving the glancing angle of X-ray incidence. 展开更多
关键词 Glancing Angle x-ray DIFFRACTION Thin films Titanium OXIDES Metal CHALCOGENIDES ELECTRODEPOSITION
下载PDF
上一页 1 2 18 下一页 到第
使用帮助 返回顶部