Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review.

Published on Mar 3, 2021in Multimedia Tools and Applications2.757
· DOI :10.1007/S11042-021-10714-5
Anuja Bhargava4
Estimated H-index: 4
(GLA University),
Atul Bansal9
Estimated H-index: 9
(GLA University)
Sources
Abstract
The universal transmission of pandemic COVID-19 (Coronavirus) causes an immediate need to commit in the fight across the whole human population. The emergencies for human health care are limited for this abrupt outbreak and abandoned environment. In this situation, inventive automation like computer vision (machine learning, deep learning, artificial intelligence), medical imaging (computed tomography, X-Ray) has developed an encouraging solution against COVID-19. In recent months, different techniques using image processing are done by various researchers. In this paper, a major review on image acquisition, segmentation, diagnosis, avoidance, and management are presented. An analytical comparison of the various proposed algorithm by researchers for coronavirus has been carried out. Also, challenges and motivation for research in the future to deal with coronavirus are indicated. The clinical impact and use of computer vision and deep learning were discussed and we hope that dermatologists may have better understanding of these areas from the study.
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#2Liming Xia (HUST: Huazhong University of Science and Technology)H-Index: 8
Last. Dinggang ShenH-Index: 122
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The worldwide spread of coronavirus disease (COVID-19) has become a threatening risk for global public health. It is of great importance to rapidly and accurately screen patients with COVID-19 from community acquired pneumonia (CAP). In this study, a total of 1658 patients with COVID-19 and 1027 CAP patients underwent thin-section CT. All images were preprocessed to obtain the segmentations of infections and lung fields. A set of handcrafted location-specific features was proposed to best captur...
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#1Asmaa Abbas (Assiut University)H-Index: 6
#2Mohammed M. Abdelsamea (BCU: Birmingham City University)H-Index: 13
Last. Mohamed Medhat Gaber (BCU: Birmingham City University)H-Index: 35
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Chest X-ray is the first imaging technique that plays an important role in the diagnosis of COVID-19 disease. Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural networks (CNN s) for image recognition and classification. However, due to the limited availability of annotated medical images, the classification of medical images remains the biggest challenge in medical diagnosis. Thanks to transfer learning, an effective m...
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#2Jin Shuo (THU: Tsinghua University)H-Index: 4
Last. Jiahong Dong (THU: Tsinghua University)H-Index: 2
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The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to reduce physician workload in regions with the outbreak, and improve the diagnosis accuracy for physicians before they could acquire enough experience with the new disease. In this paper, we present our experience in building and deploying an AI system that automatically analyzes CT images and provides the probability ...
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The Coronavirus Disease 2019 (COVID-19) pandemic continues to have a devastating effect on the health and well-being of the global population. A critical step in the fight against COVID-19 is effective screening of infected patients, with one of the key screening approaches being radiology examination using chest radiography. It was found in early studies that patients present abnormalities in chest radiography images that are characteristic of those infected with COVID-19. Motivated by this and...
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Computed tomography (CT) is the preferred imaging method for diagnosing 2019 novel coronavirus (COVID19) pneumonia. We aimed to construct a system based on deep learning for detecting COVID-19 pneumonia on high resolution CT. For model development and validation, 46,096 anonymous images from 106 admitted patients, including 51 patients of laboratory confirmed COVID-19 pneumonia and 55 control patients of other diseases in Renmin Hospital of Wuhan University were retrospectively collected. Twenty...
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Background The coronavirus disease 2019 (COVID-19) has become a global challenge since the December 2019. The hospital stay is one of the prognostic indicators, and its predicting model based on CT radiomics features is important for assessing the patients' clinical outcome. The study aimed to develop and test machine learning-based CT radiomics models for predicting hospital stay in patients with COVID-19 pneumonia. Methods This retrospective, multicenter study enrolled patients with laboratory...
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Malignant melanoma, not belongs to a common type of skin cancers but most serious because of its growth—affecting large number of people worldwide. Recent studies proclaimed that risk factors can be substantially reduced by making it almost treatable, if detected at its early stages. This timely detection and classification demand an automated system, though procedure is quite complex. In this article, a novel strategy is adopted, which not only diagnoses the skin cancer but also assigns a prope...
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Abstract In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if harnessed appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur shortly in Machine Learning, the entire community stands in front of the barrier of explainability, an inherent problem of the latest techniques brought by sub-symbolism (e.g. ensembles or Deep Neural Networks) that were not present in the last hype of AI (namely, exper...
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Background: The 2019 novel coronavirus disease (COVID-19) has been spread widely in the world, causing a huge threat to people's living environment. Objective: Under computed tomography (CT) imaging, the structure features of COVID-19 lesions are complicated and varied greatly in different cases. To accurately locate COVID-19 lesions and assist doctors to make the best diagnosis and treatment plan, a deep-supervised ensemble learning network is presented for COVID-19 lesion segmentation in CT im...
#3Mingquan Lin (Cornell University)H-Index: 5
Abstract null Age-related macular degeneration (AMD) is the leading cause of vision loss. Some patients experience vision loss over a delayed timeframe, others at a rapid pace. Physicians analyze time-of-visit fundus photographs to predict patient risk of developing late-AMD, the most severe form of AMD. Our study hypothesizes that 1) incorporating historical data improves predictive strength of developing late-AMD and 2) state-of-the-art deep-learning techniques extract more predictive image fe...
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The paper presents a comparative analysis of five Convolutional Neural Networks (CNN’s) for reliable detection of COVID-19 from chest X-ray (CXR) images. The transfer learning approach is applied to a dataset compiled from public sources, aiming at discriminating the presence of COVID-19 pathology from normal, lung opacity, and pneumonia situations. Experimental results indicate that best accuracy performances are obtained by the Resnet-50 network, while all CNN’s compare favorably with existing...
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The World Health Organization (WHO) describes COVID-19 as a pandemic that is causing a worldwide health disaster. Wearing a face mask in public places is the most effective method to curb the spread of the virus. The Internet of Things is emerging as one of the most significant innovations and playing a vital role during the pandemic. Affordable remote health monitoring devices help doctors to track quarantined patients. Our government is trying its best to control the spread of the virus. Citiz...
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#2Juan Irving Vasquez-Gomez (IPN: Instituto Politécnico Nacional)H-Index: 4
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The COVID-19 pandemic is causing a devastating effect on the health of global population. There are several efforts to prevent the spread of the virus. Among those efforts, cleaning and disinfecting public areas has become an important task. This task is not restricted to disinfection, but it is also applied to painting or precision agriculture. Current state of the art planners determine a route, but they do not consider that the plan will be executed in closed areas or they do not model the sp...
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