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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Review of Artificial Intelligence Techniques in Imaging Data Acquisition,Segmentation and Diagnosis for COVID-19 |
| Authors Name: | Sharda Jha , Sushmitha Sarraf , Rajeshwari M Savalagi , Nishvitha N.R , Assistant Professor Noushin Taj |
| Unique Id: | IJSDR2107073 |
| Published In: | Volume 6 Issue 7, July-2021 |
| Abstract: | The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world. Medical imaging such as X-ray and computed tomography (CT) plays an essential role in the global fight against COVID-19, whereas the recently emerging artificial intelligence (AI) technologies further strengthen the power of the imaging tools and help medical specialists. We hereby review the rapid responses in the community of medical imaging (empowered by AI) toward COVID-19. For example, AI-empowered image acquisition can significantly help automate the scanning procedure and also reshape the workflow with minimal contact to patients, providing the best protection to the imaging technicians. Also, AI can improve work efficiency by accurate delineation of infections in X-ray and CT images, facilitating subsequent quantification. Moreover, the computer-aided platforms help radiologists make clinical decisions, i.e., for disease diagnosis, tracking, and prognosis. In this review paper, we thus cover the entire pipeline of medical imaging and analysis techniques involved with COVID-19, including image acquisition, segmentation, diagnosis, and follow-up. |
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| Cite Article: | "Review of Artificial Intelligence Techniques in Imaging Data Acquisition,Segmentation and Diagnosis for COVID-19", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.6, Issue 7, page no.474 - 479, July-2021, Available :http://www.ijsdr.org/papers/IJSDR2107073.pdf |
| Downloads: | 000337068 |
| Publication Details: | Published Paper ID: IJSDR2107073 Registration ID:193537 Published In: Volume 6 Issue 7, July-2021 DOI (Digital Object Identifier): Page No: 474 - 479 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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