TY - JOUR
T1 - Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19
AU - Shi, Feng
AU - Wang, Jun
AU - Shi, Jun
AU - Wu, Ziyan
AU - Wang, Qian
AU - Tang, Zhenyu
AU - He, Kelei
AU - Shi, Yinghuan
AU - Shen, Dinggang
N1 - Funding Information:
January 22, 2021. This work was supported in part by the Shanghai by the virus is increasing rapidly. Up to April 9, 2020, 1,436,198 Science and Technology Foundation under Grants 18010500600 and cases of COVID-19 have been reported in over 200 countries mentProgram of ChinaunderGrant 2018YFC0116400,andinpart19QC1400600,inpart bythe NationalKey Research andDevelop- and territories, resulting in approximately 85,521 deaths (with by the Natural Science Foundation of Jiangsu Province under Grant a fatal rate of 5.95%) [1]. This has led to great public health BK20181339. (Feng Shi, Jun Wang, and Jun Shi contributed equally concern in the international community, as the World Health FengShiandDinggangShenarewith theDepartment of Re-tothiswork.)(Correspondingauthor:DinggangShen.) Organization (WHO) declared the outbreak to be a Public Health search and Development, Shanghai United Imaging Intelligence Co., Emergency of International Concern (PHEIC) on January 30, Ltd., Shanghai 200232, China (e-mail: feng.shi@united-imaging.com; 2020 and recognized it as a pandemic on March 11, 2020 [2], JunWangandJunShiarewiththeKeyLaboratoryofSpecialtyFiberdinggang.shen@gmail.com). [3].
Publisher Copyright:
© 2008-2011 IEEE.
PY - 2021
Y1 - 2021
N2 - 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. We particularly focus on the integration of AI with X-ray and CT, both of which are widely used in the frontline hospitals, in order to depict the latest progress of medical imaging and radiology fighting against COVID-19.
AB - 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. We particularly focus on the integration of AI with X-ray and CT, both of which are widely used in the frontline hospitals, in order to depict the latest progress of medical imaging and radiology fighting against COVID-19.
KW - COVID-19
KW - artificial intelligence
KW - diagnosis
KW - image acquisition
KW - segmentation
UR - http://www.scopus.com/inward/record.url?scp=85083726857&partnerID=8YFLogxK
U2 - 10.1109/RBME.2020.2987975
DO - 10.1109/RBME.2020.2987975
M3 - Review article
C2 - 32305937
AN - SCOPUS:85083726857
SN - 1937-3333
VL - 14
SP - 4
EP - 15
JO - IEEE Reviews in Biomedical Engineering
JF - IEEE Reviews in Biomedical Engineering
M1 - 9069255
ER -