Supervised and weakly supervised deep learning models for COVID-19 CT diagnosis: A systematic review
Artificial intelligence (AI) and computer vision (CV) methods become reliable to extract
features from radiological images, aiding COVID-19 diagnosis ahead of the pathogenic tests …
features from radiological images, aiding COVID-19 diagnosis ahead of the pathogenic tests …
Review and classification of AI-enabled COVID-19 CT imaging models based on computer vision tasks
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 …
strategies for diagnosing the coronavirus disease of 2019 (COVID-19) using computerized …
COVID-19 lung infection segmentation with a novel two-stage cross-domain transfer learning framework
With the global outbreak of COVID-19 in early 2020, rapid diagnosis of COVID-19 has
become the urgent need to control the spread of the epidemic. In clinical settings, lung …
become the urgent need to control the spread of the epidemic. In clinical settings, lung …
Progressive global perception and local polishing network for lung infection segmentation of COVID-19 CT images
In this paper, a progressive global perception and local polishing (PCPLP) network is
proposed to automatically segment the COVID-19-caused pneumonia infections in …
proposed to automatically segment the COVID-19-caused pneumonia infections in …
[HTML][HTML] A deep learning-based diagnosis system for COVID-19 detection and pneumonia screening using CT imaging
R Mahmoudi, N Benameur, R Mabrouk… - Applied Sciences, 2022 - mdpi.com
Background: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a global
threat impacting the lives of millions of people worldwide. Automated detection of lung …
threat impacting the lives of millions of people worldwide. Automated detection of lung …
ADU-Net: an attention dense U-Net based deep supervised DNN for automated lesion segmentation of COVID-19 from chest CT images
An automatic method for qualitative and quantitative evaluation of chest Computed
Tomography (CT) images is essential for diagnosing COVID-19 patients. We aim to develop …
Tomography (CT) images is essential for diagnosing COVID-19 patients. We aim to develop …
COLI‐Net: deep learning‐assisted fully automated COVID‐19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography …
We present a deep learning (DL)‐based automated whole lung and COVID‐19 pneumonia
infectious lesions (COLI‐Net) detection and segmentation from chest computed tomography …
infectious lesions (COLI‐Net) detection and segmentation from chest computed tomography …
[HTML][HTML] Lunginfseg: Segmenting covid-19 infected regions in lung ct images based on a receptive-field-aware deep learning framework
COVID-19 is a fast-growing disease all over the world, but facilities in the hospitals are
restricted. Due to unavailability of an appropriate vaccine or medicine, early identification of …
restricted. Due to unavailability of an appropriate vaccine or medicine, early identification of …
[HTML][HTML] A sustainable deep learning-based framework for automated segmentation of COVID-19 infected regions: Using U-Net with an attention mechanism and …
COVID-19 has been spreading rapidly, affecting billions of people globally, with significant
public health impacts. Biomedical imaging, such as computed tomography (CT), has …
public health impacts. Biomedical imaging, such as computed tomography (CT), has …
[HTML][HTML] COVLIAS 1.0Lesion vs. MedSeg: An Artificial Intelligence Framework for Automated Lesion Segmentation in COVID-19 Lung Computed Tomography Scans
Background: COVID-19 is a disease with multiple variants, and is quickly spreading
throughout the world. It is crucial to identify patients who are suspected of having COVID-19 …
throughout the world. It is crucial to identify patients who are suspected of having COVID-19 …