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Residual Feature Attentional Fusion Network for Lightweight chest ct Image Super-Resolution

Computers, Materials & Continua 2023年第6期75卷 5159-5176页

作者： Kun Yang Lei Zhao Xianghui Wang Mingyang Zhang Linyan Xue Shuang Liu Kun Liu College of Quality and Technical Supervision Hebei UniversityBaoding071002China Hebei Technology Innovation Center for Lightweight of New Energy Vehicle Power System Baoding071002China Postdoctoral Research Station of Optical Engineering Hebei UniversityBaoding071000China

The diagnosis of COVID-19 requires chest computed tomography(ct).High-resolution ct images can provide more diagnostic information to help doctors better diagnose the disease,so it is of clinical importance to study super-resolution(SR)algorithms applied to ct images to improve the reso-lution of ct ***,most of the existing SR algorithms are studied based on natural images,which are not suitable for medical images;and most of these algorithms improve the reconstruction quality by increasing the network depth,which is not suitable for machines with limited *** alleviate these issues,we propose a residual feature attentional fusion network for lightweight chest ct image super-resolution(RFAFN).Specifically,we design a contextual feature extraction block(CFEB)that can extract ct image features more efficiently and accurately than ordinary residual *** addition,we propose a feature-weighted cascading strategy(FWCS)based on attentional feature fusion blocks(AFFB)to utilize the high-frequency detail information extracted by CFEB as much as possible via selectively fusing adjacent level feature ***,we suggest a global hierarchical feature fusion strategy(GHFFS),which can utilize the hierarchical features more effectively than dense concatenation by progressively aggregating the feature information at various *** experiments show that our method performs better than most of the state-of-the-art(SOTA)methods on the COVID-19 chest ct *** detail,the peak signal-to-noise ratio(PSNR)is 0.11 dB and 0.47 dB higher on cttest1 and cttest2 at×3 SR compared to the suboptimal method,but the number of parameters and multi-adds are reduced by 22K and 0.43G,*** method can better recover chest ct image quality with fewer computational resources and effectively assist in COVID-19.

关键词： Super-resolution COVID-19 chest ct lightweight network contextual feature extraction attentional feature fusion

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COVID-19 Imaging Detection in the Context of Artificial Intelligence and the Internet of Things

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Computer Modeling in Engineering & Sciences 2022年第8期132卷 507-530页

作者： Xiaowei Gu Shuwen Chen Huisheng Zhu Mackenzie Brown School of Math and Information Technology Jiangsu Second Normal UniversityNanjing211200China State Key Laboratory of Millimeter Waves Southeast UniversityNanjing210096China School of Engineering Edith Cowan UniversityJoondalupWA 6027Australia

Coronavirus disease 2019 brings a huge burden on the medical industry all over the *** the background of artificial intelligence(AI)and Internet of Things(IoT)technologies,chest computed tomography(ct)and chest Xray(CXR)scans are becoming more intelligent,and playing an increasingly vital role in the diagnosis and treatment of *** paper will introduce the segmentation of methods and *** and ct diagnosis of COVID-19 based on deep learning,which can be widely used to fight against COVID-19.

关键词： COVID-19 medical image chest ct CXR IoMT AI

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A Novel Technique for Early Detection of COVID-19

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Computers, Materials & Continua 2021年第8期68卷 2283-2298页

作者： Mohammad Yamin Adnan Ahmed Abi Sen Zenah Mahmoud AlKubaisy Rahaf Almarzouki Department of Management Information Systems Faculty of Economics and AdministrationKing Abdulaziz UniversityJeddah21589Saudi Arabia Faculty of Computer and Information Systems Islamic University of MadinahAl MedinaSaudi Arabia

COVID-19 is a global pandemic disease,which results from a dangerous coronavirus attack,and spreads aggressively through close contacts with infected people and *** far,there is not any prescribed line of treatment for COVID-19 *** to control the disease are very limited,partly due to the lack of knowledge about technologies which could be effectively used for early detection and control the *** detection of positive cases is critical in preventing further spread,achieving the herd immunity,and saving ***,so far we do not have effective toolkits to diagnose very early detection of the *** research findings have suggested that radiology images,such as X-rays,contain significant information to detect the presence of COVID-19 virus in early ***,to detect the presence of the disease in in very early stages from the X-ray images by the naked eye is not *** Intelligence(AI)techniques,machine learning in particular,are known to be very helpful in accurately diagnosing many diseases from radiology *** paper proposes an automatic technique to classify COVID-19 patients from their computerized tomography(ct)scan *** technique is known as Advanced Inception based Recurrent Residual Convolution Neural Network(AIRRCNN),which uses machine learning techniques for classifying *** focus on the Advanced Inception based Recurrent Residual Convolution Neural Network,because we do not find it being used in the ***,we conduct principal component analysis,which is used for dimensional *** results of our method have demonstrated an accuracy of about 99%,which is regarded to be very efficient.

关键词： COVID-19 classification feature selection dimensionality reduction chest ct deep learning deep convolutional neural network AIRRCNN

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An Efficient Method for Covid-19 Detection Using Light Weight Convolutional Neural Network

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Computers, Materials & Continua 2021年第11期69卷 2475-2491页

作者： Saddam Bekhet Monagi H.Alkinani Reinel Tabares-Soto M.Hassaballah Faculty of Commerce South Valley UniversityQenaEgypt Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21959Saudi Arabia Department of Electronics and Automation Universidad Autónoma de ManizalesManizales170001Colombia Department of Computer Science Faculty of Computers and InformationSouth Valley UniversityQenaEgypt

The COVID-19 pandemic is a significant milestone in the modern history of civilization with a catastrophic effect on global wellbeing and *** situation is very complex as the COVID-19 test kits are limited,therefore,more diagnostic methods must be developed urgently.A significant initial step towards the successful diagnosis of the COVID-19 is the chest X-ray or Computed Tomography(ct),where any chest anomalies(e.g.,lung inflammation)can be easily *** hospitals possess X-ray or ct imaging equipments that can be used for early detection of *** by this,various artificial intelligence(AI)techniques have been developed to identify COVID-19 positive patients using the chest X-ray or ct ***,the advance of these AI-based systems and their highly tailored results are strongly bonded to high-end GPUs,which is not widely available in several *** paper introduces a technique for early COVID-19 diagnosis based on medical experience and light-weight Convolutional Neural Networks(CNNs),which does not require a custom hardware to run compared to currently available CNN *** proposed deep learning model is built carefully and fine-tuned by removing all unnecessary parameters and layers to achieve the light-weight attribute that could run smoothly on a normal CPU(0.54%of AlexNet parameters).This model is highly beneficial for countries where high-end GPUs are *** outcomes on some new benchmark datasets shows the robustness of the proposed technique robustness in recognizing COVID-19 with 96%accuracy.

关键词： Artificial intelligence COVID-19 chest ct chest X-ray deep learning

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Multi-Features Disease Analysis Based Smart Diagnosis for COVID-19

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Computer Systems Science & Engineering 2023年第4期45卷 869-886页

作者： Sirisati Ranga Swamy SPhani Praveen Shakeel Ahmed Parvathaneni Naga Srinivasu Abdulaziz Alhumam Department of CSE Vignan’s Institute of Management and Technology for Women GhatkesarTelanganaIndia Department of CSE PVPSITVijayawadaAndhra Pradesh520007India Department of Computer Science College of Computer Sciences and Information TechnologyKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science and Engineering-AIML VNR Vignana Jyothi Institute of Engineering and TechnologyHyderabadTelangana500090India

Coronavirus 2019(COVID-19)is the current global buzzword,putting the world at *** pandemic’s exponential expansion of infected COVID-19 patients has challenged the medical field’s resources,which are already *** established nations would not be in a perfect position to manage this epidemic correctly,leaving emerging countries and countries that have not yet begun to grow to address the *** problems can be solved by using machine learning models in a realistic way,such as by using computer-aided images during medical *** models help predict the effects of the disease outbreak and help detect the effects in the coming *** this paper,Multi-Features Decease Analysis(MFDA)is used with different ensemble classifiers to diagnose the disease’s impact with the help of Computed Tomography(ct)scan *** are various features associated with chest ct images,which help know the possibility of an individual being affected and how COVID-19 will affect the persons suffering from *** current study attempts to increase the precision of the diagnosis model by evaluating various feature sets and choosing the best combination for better *** model’s performance is assessed using Receiver Operating Characteristic(ROC)curve,the Root Mean Square Error(RMSE),and the Confusion *** is observed from the resultant outcome that the performance of the proposed model has exhibited better efficient.

关键词： chest ct COVID-19 classification ROC curves multi-feature disease analysis

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Life Time Attributable Cancer Risk Estimated Using Scanner Reported Dose Length Product during chest Computed Tomography Imaging in Young Children

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Open Journal of Radiology 2024年第2期14卷 74-82页

作者： Mousa Bakkari Khaled Soliman Abdullah Alrushoud Marwan Fahad Alosaimi Hanaa Alsheikh Abdelwahed Alhejaili Medical Physics Department Prince Sultan Military Medical City Riyadh Saudi Arabia Radiogiadnostic and Medical Imaging Department Prince Sultan Military Medical City Riyadh Saudi Arabia

This study aims to estimate the lifetime attributable cancer risk (LAR) for pediatric chest computed tomography (ct) examinations in five age groups using recently published age and region-specific conversion coefficients multiplying the widely available scanner registered dose length products (DLP) displayed on the ct console and hence calculating the Effective Dose (ED). The ED is then multiplied by the International Commission on Radiological Protection (ICRP) published risk factor for LAR. The obtained LAR values are compared with the international literature. Factors that may affect the LAR value are reported and discussed. The study included one hundred twenty five chest ct examinations for both males and females aged from less than one year to fifteen years. The patients reported data are from one single medical institution and using two ct scanners from June 2022 to December 2023. The results of this study may serve as benchmark for institutional radiation dose reference levels and risk estimation.

关键词： Cancer Risk LAR chest ct Pediatric Radiology Radiation Dose DLP

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Radiation Dose Survey of Pediatric chest Computed Tomography Examinations: A Local Diagnostic Reference Levels Approach to Patient Safety

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Journal of Applied Mathematics and Physics 2023年第7期11卷 2137-2143页

作者： Turki Alruwaili Bani Alsubaie Salman Altimyat Khaled Soliman Medical Physics Department Prince Sultan Military Medical City Riyadh Saudi Arabia Radiodiagnostic and Medical Imaging Department Prince Sultan Military Medical City Riyadh Saudi Arabia

Objectives: The aim of this work was to initially establish both age and weight driven pediatric diagnostic reference levels (DRLs) for chest computed tomography (ct) examinations performed at tertiary care medical institution. Another aim was to compare the presented data with internationally published ones. This initial data shall serve as basis for establishing a national DRLs values for pediatric diagnostic ct examinations. Methods: Dosimetric indexes were collected for the chest examination for 93 patients during the past 2 years in a tertiary care medical city. Results: The results are within and below the international reported levels for chest ct in several countries. Conclusion: Continuous monitoring of the radiation doses received by the patients in computed tomography is continuous and ongoing process in order to ensure compliance and to optimize clinical imaging protocols. More extensive data acquisition and analysis are required to allow better understanding of the contributing factors leading to less patient radiation dose while preserving the clinical image quality. .

关键词： Computed Tomography chest ct Diagnostic Reference Levels Monitoring Optimization

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Severe radiological manifestation in patients with diabetes and pulmonary tuberculosis:A cross-sectional study

Severe radiological manifestation in patients with diabetes ...

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中国防痨协会第33届全国学术大会暨中国防痨科技奖颁奖大会

作者： Peize Zhang Juan Xiong Shenlin Zhan Tantan Ren Yuxiang Wang Liang Fu Guofang Deng Department of Pulmonary Medicine & Tuberculosis The Third People's Hospital of Shenzhen School of Public Health Health Science CenterShenzhen University

Purpose Diabetes mellitus(DM) is believed to affect tuberculosis(TB) at multiple levels in disease control and treatment efficacy,but clinical and radiological presentation resulting from interaction of the two diseases is not *** conducted a retrospective study to investigate how glycemic control impacts radiological and clinical manifestations in TB *** A cross-sectional study was conducted on data obtained from medical records of 438 patients confirmed with TB-DM comorbidity at The Third people’s hospital of Shenzhen from April 1,2014 to April 30,*** ct images were reviewed,and patients were divided into subgroups according to lung cavitation:with and without cavities,and number of segments showing pulmonary infiltration:8 segment *** then compared clinical parameters between these *** The median age of the patients was 50.0 years(IQR 43.3-56) and 86%(n=375) of them were *** cavities were found in 80.8% patients.42.7% and 27.2% patients were seen to have infiltration involving 4-8 and>8 lung segments *** presented with cavitation and infiltration involving a greater number of lung segments had significantly higher values of WBC,MONO%,GRA%,CRP,lower LYN% level and higher bacterial burden in sputum(Pct level between the groups regardless of presence or absence of lung cavity(P>0.9 and P=0.1 respectively).Lower HGB,ALB and higher Pct were observed in patients with infiltration involving more lung ***:Hyper-inflammation in peripheral blood was significantly associated with cavity and the number of lung *** was significantly associated with the development of lung *** control and inflammation influenced radiographic manifestations in patients with TB-DM.

关键词： Diabetes mellitus HbA1C Tuberculosis Lung cavity Radiography lung infiltration chest ct

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