COVID-19 image classification using deep learning: Advances, challenges and opportunities

P Aggarwal, NK Mishra, B Fatimah, P Singh… - Computers in Biology …, 2022‏ - Elsevier
Abstract Corona Virus Disease-2019 (COVID-19), caused by Severe Acute Respiratory
Syndrome-Corona Virus-2 (SARS-CoV-2), is a highly contagious disease that has affected …

Application of deep learning techniques in diagnosis of covid-19 (coronavirus): a systematic review

YH Bhosale, KS Patnaik - Neural processing letters, 2023‏ - Springer
Covid-19 is now one of the most incredibly intense and severe illnesses of the twentieth
century. Covid-19 has already endangered the lives of millions of people worldwide due to …

On the analyses of medical images using traditional machine learning techniques and convolutional neural networks

S Iqbal, A N. Qureshi, J Li, T Mahmood - Archives of Computational …, 2023‏ - Springer
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …

[HTML][HTML] Lung-EffNet: Lung cancer classification using EfficientNet from CT-scan images

R Raza, F Zulfiqar, MO Khan, M Arif, A Alvi… - … Applications of Artificial …, 2023‏ - Elsevier
Lung cancer (LC) remains a leading cause of death worldwide. Early diagnosis is critical to
protect innocent human lives. Computed tomography (CT) scans are one of the primary …

A fully automated deep learning-based network for detecting COVID-19 from a new and large lung CT scan dataset

M Rahimzadeh, A Attar, SM Sakhaei - Biomedical Signal Processing and …, 2021‏ - Elsevier
This paper aims to propose a high-speed and accurate fully-automated method to detect
COVID-19 from the patient's chest CT scan images. We introduce a new dataset that …

COVID-19 lung CT image segmentation using deep learning methods: U-Net versus SegNet

A Saood, I Hatem - BMC Medical Imaging, 2021‏ - Springer
Background Currently, there is an urgent need for efficient tools to assess the diagnosis of
COVID-19 patients. In this paper, we present feasible solutions for detecting and labeling …

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 …

Applications of artificial intelligence in battling against covid-19: A literature review

M Tayarani - Chaos, Solitons and Fractals, 2020‏ - researchprofiles.herts.ac.uk
Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …

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 …

Hyperspectral pathology image classification using dimension-driven multi-path attention residual network

X Zhang, W Li, C Gao, Y Yang, K Chang - Expert Systems with Applications, 2023‏ - Elsevier
Hyperspectral imaging technology (HSI) can capture pathological tissue's spatial and
spectral information simultaneously, with wide coverage and high accuracy characteristics …