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COVID−19 Detection using Deep Learning and Ultrasound Imaging
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 183 - Number 32 |
| Year of Publication: 2021 |
| Authors: J.P. Gaidhani, Harshada Gunjal, Sayli Waghmare, Akanksha Gatkal, Gauri Kabra |
10.5120/ijca2021921709
|
J.P. Gaidhani, Harshada Gunjal, Sayli Waghmare, Akanksha Gatkal, Gauri Kabra . COVID−19 Detection using Deep Learning and Ultrasound Imaging. International Journal of Computer Applications. 183, 32 ( Oct 2021), 18-22. DOI=10.5120/ijca2021921709
Abstract
There has been a rapid increase in growth of Covid-19 which has left a problem of efficient diagnosis and cheap diagnosis of Covid-19 patients. Using medical imaging techniques Like CT and X-ray combined with Deep learning are proving to be quite effective in the Diagnostic process. CT scans are widely used for the diagnostics they have been proven to be fast and have shown promising results and are sensitive even when the PCR test fails. But there are some flaws with CT scans like they are hard to sterilize, expensive and they are highly radiating. In this paper we have used ultrasound imaging technique which is cheaper, easy to use, fast and safe. We have Gathered Data set from various Sources of around 1000 images which consist of healthy lungs, Covid affected lungs and bacterial Pneumonia Affected Lungs. This has been assembled from various data sources which have been processed for deep learning Models and are open access. We have trained a deep learning model which hasa accuracy.
References
- WHO, “Laboratory testing strategy recommendations for COVID19: Interim guidance,” Tech. Rep.,2020. [Online]. Available: https://apps.who.int/iris/bitstream/handle/10665/331509/WHOCOVID-19-lab testing-2020.1-eng.pdf
- Deepak A Vidhate, Parag Kulkarni, “Performance comparison of multiagent cooperative reinforcement learning algorithms for dynamic decision making in retail shop application”, International Journal of Computational Systems Engineering, Inderscience Publishers (IEL), Volume 5, Issue 3, pp 169-178, 2019.
- R. Niehus, P. M. D. Salazar, A. Taylor, and M. Lipsitch, “Quantifying bias of COVID-19 prevalence and severity estimates in Wuhan, China that depend on reported cases in international travelers,” medRxiv, p.2020.02.13, feb 2020.
- Deepak A Vidhate, Parag Kulkarni, “A Framework for Dynamic Decision Making by Multi-agent Cooperative Fault Pair Algorithm (MCFPA) in Retail Shop Application”, Information and Communication Technology for Intelligent Systems, Springer, Singapore, pp 693-703, 2019.
- Y. Yang et al., “Evaluating the accuracy of di_erent respiratory specimens in the laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections,” medRxiv, p. 2020.02.11., feb 2020
- Deepak A Vidhate, Parag Kulkarni, “A Novel Approach by Cooperative Multiagent Fault Pair Learning (CMFPL)” Communications in Computer and Information Science, Springer, Singapore, Volume 905, pp 352-361,2018.
- M. E. H. Chowdhury et al., "Can AI Help in Screening Viral and COVID-19 Pneumonia?" in IEEE Access, vol. 8, pp. 132665-132676, 2020, DOI: 10.1109/ACCESS.2020.3010287.
- Deepak A. Vidhate and Parag Kulkarni, “Expertise Based Cooperative Reinforcement Learning Methods (ECRLM)”, International Conference on Information & Communication Technology for Intelligent System, Springer book series Smart Innovation, Systems and Technologies(SIST, volume 84), Cham, pp 350-360, 2017.
- J. C. Monteral. (2020). COVID-Chestxray Database. Available: https://github.com/ieee8023/covid-chestxray-dataset
- Deepak A. Vidhate and Parag Kulkarni "Innovative Approach Towards Cooperation Models for Multi-agent Reinforcement Learning (CMMARL) "International Conference on Smart Trends for Information Technology and Computer Communications Springer, Singapore, pp. 468-478, 2016.
- Alqudah, Ali Mohammad; Qazan, Shoroq (2020), “Augmented COVID-19 X-ray Images Dataset”,Mendeley Data, v4 http://dx.doi.org/10.17632/2fxz4px6d8.4
- Deepak A. Vidhate and Parag Kulkarni, “Enhanced Cooperative Multi-agent Learning Algorithms (ECMLA) using Reinforcement Learning” International Conference on Computing, Analytics and Security Trends (CAST), IEEE Xplorer, pp 556 - 561, 2017.
- Abiyev R. H., Ma’aitah M. K. S., “Deep Convolutional Neural Networks for Chest Diseases Detection”,Journal of Healthcare Engineering, 2018.
- Deepak A. Vidhate and Parag Kulkarni, “Exploring Cooperative Multi-agent Reinforcement Learning Algorithm (CMRLA) for Intelligent Traffic Signal Control”, Smart Trends in Information Technology and Computer Communications. SmartCom 2017, Volume 876, pp 71-81,2018.
- T. Liang, "Handbook of COVID-19 prevention and treatment," The First Affiliated Hospital, ZhejiangUniversity School of Medicine Compiled According to Clinical Experience, 2020.
- Deepak A Vidhate and Parag Kulkarni, “A Novel Approach for Dynamic Decision Making by Reinforcement Learning-Based Cooperation Methods (RLCM)”, International Conference on Intelligent Computing and Applications, Springer, Singapore, 401-411, 2018.
- Soyoun Kim, Dong-Min Kim, and Baeckseung Lee. Insufficient sensitivity of rna dependent rna polymerase gene of sars-cov-2 viral genome as confirmatory test using korean covid-19 cases. 2020.
- Deepak A Vidhate and Shruti S Pophale, “Depression Scale Recognition Over Fusion of Visual and Vocal Expression using Artificial Intellectual Method”, International Journal of Computer Applications (IJCA), Volume 183, Issue 24, Pages 16-19,2021.
- Roman Kalkreuth and Paul Kaufmann. Covid-19: A survey on public medical imaging data resources.arXiv preprint arXiv:2004.04569, 2020.
- Deepak A Vidhate and Mansi Palve, “Customer Relationship Management: An IT Success as Multifunctional Domain and it’s Fututre Directions”, International Journal of Computer Applications (IJCA), Volume 183, Issue 19, Pages 30-34,2021.
- MJ Smith, SA Hayward, SM Innes, and A Miller. Point-of-care lung ultrasound in patients with covid19–a narrative review. Anaesthesia, 2020
- MdZahangirAlom, MM Shaifur Rahman, MstShamimaNasrin, Tarek M Taha, and Vijayan K Asari.Covidmtnet : Covid19detectionwithmulti-taskdeeplearningapproaches:arXiv; pagesarXiv˘2004; 2020:
- Jianpeng Zhang, YutongXie, Yi Li, Chunhua Shen, and Yong Xia. Covid-19 screening on chest x-ray images using deep learning based anomaly detection. arXiv preprint arXiv:2003.12338, 2020.
- Paulo ViniciusMasnik, Roberto Alexandre Dias and Mario De Noronha Neto. Detection of Myocardial Infarction in Electrocardiograms using Machine Learning. International Journal of Computer Applications 183(9):12-19, June 2021.
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