Review of Artificial Intelligence Techniques in Imaging Data Acquisition,Segmentation and Diagnosis for COVID-19

Sharda Jha , Sushmitha Sarraf , Rajeshwari M Savalagi , Nishvitha N.R , Assistant Professor Noushin Taj

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.

Published Paper   E-Certificate

"Review of Artificial Intelligence Techniques in Imaging Data Acquisition,Segmentation and Diagnosis for COVID-19", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.6, Issue 7, page no.474 - 479, July-2021, Available :https://ijsdr.org/papers/IJSDR2107073.pdf

Volume 6 Issue 7, July-2021

Pages : 474 - 479

Paper Reg. ID: IJSDR_193537

Published Paper Id: IJSDR2107073

Downloads: 000347187

Research Area: Engineering

Country: Tumkur, Karanataka, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2107073

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2107073

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition