Integrative analysis for COVID-19 patient outcome prediction
While image analysis of chest computed tomography (CT) for COVID-19 diagnosis has been
intensively studied, little work has been performed for image-based patient outcome …
intensively studied, little work has been performed for image-based patient outcome …
AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia
G Chassagnon, M Vakalopoulou, E Battistella… - Medical image …, 2021 - Elsevier
Abstract Coronavirus disease 2019 (COVID-19) emerged in 2019 and disseminated around
the world rapidly. Computed tomography (CT) imaging has been proven to be an important …
the world rapidly. Computed tomography (CT) imaging has been proven to be an important …
Fully automated unified prognosis of Covid-19 chest X-ray/CT scan images using Deep Covix-Net model
DN Vinod, BR Jeyavadhanam, AM Zungeru… - Computers in biology …, 2021 - Elsevier
Abstract SARS-COV2 (Covid-19) prevails in the form of multiple mutant variants causing
pandemic situations around the world. Thus, medical diagnosis is not accurate. Although …
pandemic situations around the world. Thus, medical diagnosis is not accurate. Although …
CARes‐UNet: Content‐aware residual UNet for lesion segmentation of COVID‐19 from chest CT images
Abstract Purpose Coronavirus disease 2019 (COVID‐19) has caused a serious global
health crisis. It has been proven that the deep learning method has great potential to assist …
health crisis. It has been proven that the deep learning method has great potential to assist …
A multi-agent deep reinforcement learning approach for enhancement of COVID-19 CT image segmentation
Currently, most mask extraction techniques are based on convolutional neural networks
(CNNs). However, there are still numerous problems that mask extraction techniques need …
(CNNs). However, there are still numerous problems that mask extraction techniques need …
COVID-view: Diagnosis of COVID-19 using Chest CT
Significant work has been done towards deep learning (DL) models for automatic lung and
lesion segmentation and classification of COVID-19 on chest CT data. However …
lesion segmentation and classification of COVID-19 on chest CT data. However …
Automated quantification of CT patterns associated with COVID-19 from chest CT
S Chaganti, P Grenier, A Balachandran… - Radiology: Artificial …, 2020 - pubs.rsna.org
Purpose To present a method that automatically segments and quantifies abnormal CT
patterns commonly present in COVID-19, namely ground-glass opacities and …
patterns commonly present in COVID-19, namely ground-glass opacities and …
[HTML][HTML] COVID-19 infection localization and severity grading from chest X-ray images
The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems
incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 …
incapable to diagnose and test patients at the required rate. Given the effects of COVID-19 …
A survey of machine learning-based methods for COVID-19 medical image analysis
K Sailunaz, T Özyer, J Rokne, R Alhajj - Medical & Biological Engineering …, 2023 - Springer
The ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in
6.6 million deaths with more than 637 million people infected after only 30 months since the …
6.6 million deaths with more than 637 million people infected after only 30 months since the …
Customized efficient neural network for COVID-19 infected region identification in CT images
Background: In the field of biomedical imaging, radiomics is a promising approach that aims
to provide quantitative features from images. It is highly dependent on accurate identification …
to provide quantitative features from images. It is highly dependent on accurate identification …