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Chest Radiographs Images Retrieval Using Deep Learning Networks
2022
Bulletin of Electrical Engineering and Informatics
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COVID-19 (–)) for X-ray and CT-scan respectively. ...
Content-based image retrieval in terms of medical images offers such a facility based on visual feature descriptor and similarity measurements. ...
ACKNOWLEDGEMENTS The authors of this work would like to thank Mustansiriyah University http://www.uomustansiriyah.edu.iq in Baghdad, Iraq for its support. ...
doi:10.11591/eei.v11i3.3478
fatcat:kgpitveycfa5hk4in6pv6jav7e
Deep Learning applications for COVID-19
2021
Journal of Big Data
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Deep Learning has additionally been utilized in Spread Forecasting for Epidemiology. Our literature review has found many examples of Deep Learning systems to fight COVID-19. ...
We begin by evaluating the current state of Deep Learning and conclude with key limitations of Deep Learning for COVID-19 applications. ...
Acknowledgements We would like to thank the reviewers in the Data Mining and Machine Learning Laboratory at Florida Atlantic University. ...
doi:10.1186/s40537-020-00392-9
pmid:33457181
pmcid:PMC7797891
fatcat:aokxo63z2rhdpfxo3egyf3xpcm
Is Medical Chest X-ray Data Anonymous?
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2103.08562v2 fatcat:63yk6roervhk3jylnwdurzufcuOther Versions
Furthermore, we achieve an AUC of up to 0.9870 and a precision@1 of up to 0.9444 when evaluating our trained networks on CheXpert and the COVID-19 Image Data Collection. ...
To the best of our knowledge, we are the first to show that a well-trained deep learning system is able to recover the patient identity from chest X-ray data. ...
Acknowledgements The research leading to these results has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (ERC grant no ...
arXiv:2103.08562v3
fatcat:6snwohaamvgqlokdpov5dn3ggq
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature
2020
IEEE Transactions on Big Data
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Because a large portion of figures in COVID-19 articles are not CXR or CT, we designed a deep-learning model to distinguish them from other figure types and to classify them accordingly. ...
DL) performance for the classification of COVID-19 and non-COVID-19 CT. (2) We collected CT images of influenza, another common infectious respiratory illness that may present similarly to COVID-19, and ...
These articles contain rich chest radiographs and CT images that are helpful for scientists and clinicians in describing COVID-19 cases. ...
doi:10.1109/tbdata.2020.3035935
pmid:33997112
pmcid:PMC8117951
fatcat:kk25kejyo5bzlhlhk3dbbr6rda
Fully automatic deep convolutional approaches for the analysis of Covid-19 using chest X-ray images
[article]
2020
medRxiv
pre-print
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Among its applications, chest X-ray images are frequently used for an early diagnostic/screening of Covid-19 disease, given the frequent pulmonary impact in the patients, critical issue to prevent further ...
In this work, we propose complementary fully automatic approaches for the classification of chest X-ray images under the analysis of 3 different categories: Covid-19, pneumonia and healthy cases. ...
Acknowledgement This work is supported by the Instituto de Salud Carlos III, Government of Spain and FEDER funds of the European Union through the DTS18/00136 research projects and by the Ministerio de ...
doi:10.1101/2020.05.01.20087254
fatcat:is2mjeoi6rdsdi2mr7ga7wezmi
COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature
[article]
2020
arXiv
pre-print
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compared clinical symptoms and clinical findings of COVID-19 vs. those of influenza to demonstrate the disease differences in the scientific publications. ...
for the classification of COVID-19 and non-COVID-19 CT. (2) We collected CT images of influenza and trained a DL baseline to distinguish a diagnosis of COVID-19, influenza, or normal or other types of ...
Acknowledgment This research was supported in part by the Intramural Research Programs of the National Library of Medicine (NLM) and National Institutes of Health (NIH) Clinical Center. ...
arXiv:2006.06177v2
fatcat:wjs7vci25zgx5mimtpnliqa3wu
A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)
2021
IEEE Access
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This paper aims to overview the recently developed systems based on deep learning techniques using different medical imaging modalities like Computer Tomography (CT) and X-ray. ...
This review specifically discusses the systems developed for COVID-19 diagnosis using deep learning techniques and provides insights on well-known data sets used to train these networks. ...
Class imbalance is another big issue for deep learning based COVID-19 diagnosis systems. Data related to COVID-19 exist far less than other common lung diseases in chest X-ray and CT images. ...
doi:10.1109/access.2021.3058537
pmid:34976571
pmcid:PMC8675557
fatcat:d52pbcisz5gufdew4bjwiex7ca
Study of Different Deep Learning Methods for Coronavirus (COVID-19) Pandemic: Taxonomy, Survey and Insights
2022
Sensors
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This research seeks to provide an overview of novel deep learning-based applications for medical imaging modalities, computer tomography (CT) and chest X-rays (CXR), for the detection and classification ...
Then, utilizing deep learning techniques, we present an overview of systems created for COVID-19 detection and classification. ...
Institutional Review Board Statement: Not applicable.
Informed Consent Statement: Not applicable. ...
doi:10.3390/s22051890
pmid:35271037
pmcid:PMC8915023
fatcat:yzso2egndjd63ec2ykqppub7tm
A Review on Deep Learning Techniques for the Diagnosis of Novel Coronavirus (COVID-19)
[article]
2020
arXiv
pre-print
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This paper aims to overview the recently developed systems based on deep learning techniques using different medical imaging modalities like Computer Tomography (CT) and X-ray. ...
This review specifically discusses the systems developed for COVID-19 diagnosis using deep learning techniques and provides insights on well-known data sets used to train these networks. ...
A total of 339,271 images were taken where 144 images for COVID-19 patients, 108,948 samples of pneumonia and bacteria except COVID-19, 224,316 chest radiographs of bacteria and pneumonia, and 5,863 paediatric ...
arXiv:2008.04815v1
fatcat:zxfzqyq6hvhhhdgj3jdqapbc5q
Classification Framework for COVID-19 Diagnosis Based on Deep CNN Models
2022
Intelligent Automation and Soft Computing
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This paper introduces a DCNN (Deep Convolutional Neural Network) framework for chest X-ray and CT image classification based on TL (Transfer Learning). ...
COVID-19 first appeared in China, Wuhan, and then it has exploded in the whole world with a very bad impact on our daily life. ...
The need to interpret radiographic images has inspired a series of deep learning AI systems [3] , which have shown promising accuracy results in detecting COVID-19 cases from radiographic imagery [4, ...
doi:10.32604/iasc.2022.020386
fatcat:nxt3egdlcjchrnhnij5evvjsju
Deep learning applications in pulmonary medical imaging: recent updates and insights on COVID-19
2020
Machine Vision and Applications
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This paper reviews the development of deep learning applications in medical image analysis targeting pulmonary imaging and giving insights of contributions to COVID-19. ...
Likewise, deep learning applications (DL) on pulmonary medical images emerged to achieve remarkable advances leading to promising clinical trials. ...
Deep learning applications to COVID-19 medical imaging analysis Contributions to deep learning applications for COVID-19 that were published in pre-prints until the end of May 2020 were excluded from the ...
doi:10.1007/s00138-020-01101-5
pmid:32834523
pmcid:PMC7386599
fatcat:tkkylrptc5hkpoj52hjs3kuttu
COVID-19 Severity Classification on Chest X-ray Images
[article]
2022
arXiv
pre-print
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In this work, we classify covid images based on the severity of the infection. First, we pre-process the X-ray images using a median filter and histogram equalization. ...
Biomedical imaging analysis combined with artificial intelligence (AI) methods has proven to be quite valuable in order to diagnose COVID-19. ...
Abinash Mishra, MD, (Government Hospital; Odisha, India) for classifying the lungs images as per their severity. ...
arXiv:2205.12705v1
fatcat:fky325h5qff75i7n3kztru2p6y
Prediction of Patient Management in COVID-19 Using Deep Learning-Based Fully Automated Extraction of Cardiothoracic CT Metrics and Laboratory Findings
2021
Korean Journal of Radiology
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To extract pulmonary and cardiovascular metrics from chest CTs of patients with coronavirus disease 2019 (COVID-19) using a fully automated deep learning-based approach and assess their potential to predict ...
Multiple pulmonary and cardiovascular metrics were extracted from the chest CT images using deep learning. ...
Additionally, we appreciate the great support of our research team, namely Rita Achermann, Ivan Nesic, Joshy Cyriac, and Bram Stieltjes. ...
doi:10.3348/kjr.2020.0994
pmid:33686818
pmcid:PMC8154782
fatcat:5cbqsomtsnd7dkojsag74al3uu
The Progress of Medical Image Semantic Segmentation Methods for Application in COVID-19 Detection
2021
Computational Intelligence and Neuroscience
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The traditional method and the published dataset for segmentation are reviewed in the first step. ...
, multistage and multifeature methods, supervised methods, semiregulatory methods, and nonregulatory methods, are then thoroughly explored in current methods based on the deep neural network. ...
for publication. ...
doi:10.1155/2021/7265644
pmid:34840563
pmcid:PMC8611358
fatcat:6xsjrgiabjat5c6uinwa2kbyay
Role of Deep Learning in Early Detection of COVID-19: Scoping Review
2021
Computer Methods and Programs in Biomedicine Update
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All studies used deep learning for detection of COVID-19 cases in early stage based on different diagnostic modalities. ...
Deep Learning (DL) is a branch of Artificial intelligence (AI) applications, the recent growth of DL includes features that could be helpful in fighting the COVID-19 pandemic. ...
learning, artificial intelligence and deep learning" and the target disease "Coronavirus and COVID-19". total retrieved studies in (Appendix A).
. ...
doi:10.1016/j.cmpbup.2021.100025
pmid:34345877
pmcid:PMC8321699
fatcat:vdvd47unpvaslo3ie2oofyxbfa
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