Literature DB >> 32305937

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

Feng Shi, Jun Wang, Jun Shi, Ziyan Wu, Qian Wang, Zhenyu Tang, Kelei He, Yinghuan Shi, Dinggang Shen.   

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. 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.

Entities:  

Mesh:

Year:  2021        PMID: 32305937     DOI: 10.1109/RBME.2020.2987975

Source DB:  PubMed          Journal:  IEEE Rev Biomed Eng        ISSN: 1937-3333


  218 in total

Review 1.  What is new in computer vision and artificial intelligence in medical image analysis applications.

Authors:  Jimena Olveres; Germán González; Fabian Torres; José Carlos Moreno-Tagle; Erik Carbajal-Degante; Alejandro Valencia-Rodríguez; Nahum Méndez-Sánchez; Boris Escalante-Ramírez
Journal:  Quant Imaging Med Surg       Date:  2021-08

2.  Review of deep learning: concepts, CNN architectures, challenges, applications, future directions.

Authors:  Laith Alzubaidi; Jinglan Zhang; Amjad J Humaidi; Ayad Al-Dujaili; Ye Duan; Omran Al-Shamma; J Santamaría; Mohammed A Fadhel; Muthana Al-Amidie; Laith Farhan
Journal:  J Big Data       Date:  2021-03-31

3.  Self-Ensembling Co-Training Framework for Semi-Supervised COVID-19 CT Segmentation.

Authors:  Caizi Li; Li Dong; Qi Dou; Fan Lin; Kebao Zhang; Zuxin Feng; Weixin Si; Xuesong Deng; Zhe Deng; Pheng-Ann Heng
Journal:  IEEE J Biomed Health Inform       Date:  2021-11-05       Impact factor: 5.772

4.  FluNet: An AI-Enabled Influenza-Like Warning System.

Authors:  Ryan J Ward; Fred Paul Mark Jjunju; Isa Kabenge; Rhoda Wanyenze; Elias J Griffith; Noble Banadda; Stephen Taylor; Alan Marshall
Journal:  IEEE Sens J       Date:  2021-09-16       Impact factor: 3.301

Review 5.  Tools and Techniques for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/COVID-19 Detection.

Authors:  Seyed Hamid Safiabadi Tali; Jason J LeBlanc; Zubi Sadiq; Oyejide Damilola Oyewunmi; Carolina Camargo; Bahareh Nikpour; Narges Armanfard; Selena M Sagan; Sana Jahanshahi-Anbuhi
Journal:  Clin Microbiol Rev       Date:  2021-05-12       Impact factor: 26.132

Review 6.  The Promise of AI in Detection, Diagnosis, and Epidemiology for Combating COVID-19: Beyond the Hype.

Authors:  Musa Abdulkareem; Steffen E Petersen
Journal:  Front Artif Intell       Date:  2021-05-14

7.  Covid-19 Imaging Tools: How Big Data is Big?

Authors:  K C Santosh; Sourodip Ghosh
Journal:  J Med Syst       Date:  2021-06-03       Impact factor: 4.460

8.  Automated COVID-19 Detection from Chest X-Ray Images: A High-Resolution Network (HRNet) Approach.

Authors:  Sifat Ahmed; Tonmoy Hossain; Oishee Bintey Hoque; Sujan Sarker; Sejuti Rahman; Faisal Muhammad Shah
Journal:  SN Comput Sci       Date:  2021-05-25

9.  COVID-19 diagnosis from CT scans and chest X-ray images using low-cost Raspberry Pi.

Authors:  Khalid M Hosny; Mohamed M Darwish; Kenli Li; Ahmad Salah
Journal:  PLoS One       Date:  2021-05-11       Impact factor: 3.240

Review 10.  The frontier of live tissue imaging across space and time.

Authors:  Qiang Huang; Aliesha Garrett; Shree Bose; Stephanie Blocker; Anne C Rios; Hans Clevers; Xiling Shen
Journal:  Cell Stem Cell       Date:  2021-04-01       Impact factor: 24.633

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