A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises

SK Zhou, H Greenspan, C Davatzikos… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …

Deep learning and medical image analysis for COVID-19 diagnosis and prediction

T Liu, E Siegel, D Shen - Annual review of biomedical …, 2022 - annualreviews.org
The coronavirus disease 2019 (COVID-19) pandemic has imposed dramatic challenges to
health-care organizations worldwide. To combat the global crisis, the use of thoracic …

Automated detection and forecasting of covid-19 using deep learning techniques: A review

A Shoeibi, M Khodatars, M Jafari, N Ghassemi… - Neurocomputing, 2024 - Elsevier
Abstract In March 2020, the World Health Organization (WHO) declared COVID-19 a global
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …

COVID-19 CT image synthesis with a conditional generative adversarial network

Y Jiang, H Chen, M Loew, H Ko - IEEE Journal of Biomedical …, 2020 - ieeexplore.ieee.org
Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic that has spread
rapidly since December 2019. Real-time reverse transcription polymerase chain reaction …

[HTML][HTML] Role of machine learning techniques to tackle the COVID-19 crisis: systematic review

HB Syeda, M Syed, KW Sexton, S Syed… - JMIR medical …, 2021 - medinform.jmir.org
Background: SARS-CoV-2, the novel coronavirus responsible for COVID-19, has caused
havoc worldwide, with patients presenting a spectrum of complications that have pushed …

Automated assessment of COVID-19 reporting and data system and chest CT severity scores in patients suspected of having COVID-19 using artificial intelligence

N Lessmann, CI Sánchez, L Beenen, LH Boulogne… - Radiology, 2021 - pubs.rsna.org
Background The coronavirus disease 2019 (COVID-19) pandemic has spread across the
globe with alarming speed, morbidity, and mortality. Immediate triage of patients with chest …

Semi-supervised segmentation of radiation-induced pulmonary fibrosis from lung CT scans with multi-scale guided dense attention

G Wang, S Zhai, G Lasio, B Zhang, B Yi… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Computed Tomography (CT) plays an important role in monitoring radiation-induced
Pulmonary Fibrosis (PF), where accurate segmentation of the PF lesions is highly desired for …

D2A U-Net: Automatic segmentation of COVID-19 CT slices based on dual attention and hybrid dilated convolution

X Zhao, P Zhang, F Song, G Fan, Y Sun, Y Wang… - Computers in biology …, 2021 - Elsevier
Abstract Coronavirus Disease 2019 (COVID-19) has become one of the most urgent public
health events worldwide due to its high infectivity and mortality. Computed tomography (CT) …

On the role of artificial intelligence in medical imaging of COVID-19

J Born, D Beymer, D Rajan, A Coy, VV Mukherjee… - Patterns, 2021 - cell.com
Although a plethora of research articles on AI methods on COVID-19 medical imaging are
published, their clinical value remains unclear. We conducted the largest systematic review …

Review and classification of AI-enabled COVID-19 CT imaging models based on computer vision tasks

H Hassan, Z Ren, H Zhao, S Huang, D Li… - Computers in biology …, 2022 - Elsevier
This article presents a systematic overview of artificial intelligence (AI) and computer vision
strategies for diagnosing the coronavirus disease of 2019 (COVID-19) using computerized …