COVID-19 DETECTION - THE COMPARISON
Abstract & Details
Research Area
Electronics and Communication Engineering
Keywords
CT
CNN
VGG16
Mobile net
Densenet121
Xception
Efficient net
NAS Net
Abstract
A larger epidemic includes the coronavirus disease 2019 (Covid-19), which is brought on by the coronavirus Z2 (SARS-CoV-2) that causes severe acute respiratory syndrome. The virus is quickly spreading and infecting more people. Actual head diagnosis Polymerase chain reaction test for reverse transcription. Additional quick and accessible diagnostic tools are required because the solution time and cost of this test are exorbitant.
The rapid increase in covid infection peoples is enormous. The healthcare system across world-wide with having only limited testing kits, so it is impossible for every covid patient with respiratory illness to test using normal techniques.
Those tests are also have long turn over time and very limited sensitivity. So, X-ray machines are already in use it may help to quarantine high risk covid affected patients stint test results are awaited.
The image-based diagnosis sequence for COVID-19, using a thoracic CT scan as an example. A technician instructs and assists each individual in posing on the patient bed, after which CT scan images are collected in a single breath-hold. The radiologists' best settings for the scans are used from the Depending on the patient's body type, the costophrenic angle may be superior to the upper thoracic inlet. Reconstructed CT images are then sent via picture archiving and communication systems (PACS) for additional analysis and diagnosis using the obtained data. An innovative method in the field of medical imaging called artificial intelligence (AI) made a significant contribution to the fight against COVID-19. In comparison to the traditional imaging workflow, which depends mainly on human labour, AI enables safer, more precise, and more effective imaging solutions. The specialised imaging platform, segmentation of the lung infection region, clinical evaluation and diagnosis, and basic and clinical research, are among the AI-powered applications in COVID-19Z. Furthermore, various commercial solutions have been created that successfully integrate AI into ZcombatZCOVID-19 and clearly demonstrate the technology's capabilities.
Due to the significance of AI in every part of COVID-19 image-based analysis, the focus of this review will be on how AI-enabled medical imaging contributes to the fight against disease. First, we'll go through intelligent imaging platforms for COVID-19, Next, we'll discuss popular machine learning techniques used in imaging workflow, including segmentation, diagnosis, and prognosis. A number of publicly accessible datasets are also discussed.
The increased likelihood of occupational virus exposure makes healthcare practitioners particularly vulnerable. Priority is provided to imaging specialists and technicians in order to prevent any dangerous viral interactions. Personal protection equipment (PPE) and specialised imaging facilities are also available and procedures may be considered, which are critical in reducing hazards and saving lives.
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Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Namratha R | Sri Siddhartha institute of technology, Karnataka, India |
| 2 | Anitha Devi MD | Sri Siddhartha institute of technology, Karnataka, India |
| 3 | MZ Kurian | Sri Siddhartha institute of technology, Karnataka, India |
How to Cite
Use the following formats to cite this article in your research.
APA Style
R, Namratha, MD, Anitha Devi, & Kurian, MZ (2022). COVID-19 DETECTION - THE COMPARISON. International Journal of Advance Research and Innovative Ideas In Education, 8(4), 2553-2557.
MLA Style
R, Namratha, et al. "COVID-19 DETECTION - THE COMPARISON." International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 4, 2022, pp. 2553-2557.
IEEE Style
Namratha R, Anitha Devi MD, and MZ Kurian, "COVID-19 DETECTION - THE COMPARISON," International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 4, pp. 2553-2557, 2022.
Vancouver Style
R Namratha, MD Anitha Devi, Kurian MZ. COVID-19 DETECTION - THE COMPARISON. International Journal of Advance Research and Innovative Ideas In Education. 2022;8(4):2553-2557.
Harvard Style
R, Namratha, MD, Anitha Devi, & Kurian, MZ (2022) 'COVID-19 DETECTION - THE COMPARISON', International Journal of Advance Research and Innovative Ideas In Education, 8(4), pp. 2553-2557.
Chicago Style
R, Namratha, Anitha Devi MD, and MZ Kurian. "COVID-19 DETECTION - THE COMPARISON." International Journal of Advance Research and Innovative Ideas In Education 8, no. 4 (2022): 2553-2557.
Turabian Style
R, Namratha, Anitha Devi MD, and MZ Kurian. "COVID-19 DETECTION - THE COMPARISON." International Journal of Advance Research and Innovative Ideas In Education 8, no. 4 (2022): 2553-2557.
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