A new approach for computer-aided detection of coronavirus (COVID-19) from CT and X-ray images using machine learning methods
A Saygılı - Applied Soft Computing, 2021 - Elsevier
The COVID-19 outbreak has been causing a global health crisis since December 2019. Due
to this virus declared by the World Health Organization as a pandemic, the health authorities …
to this virus declared by the World Health Organization as a pandemic, the health authorities …
A review on the use of deep learning for medical images segmentation
M Aljabri, M AlGhamdi - Neurocomputing, 2022 - Elsevier
Deep learning (DL) algorithms have rapidly become a robust tool for analyzing medical
images. They have been used extensively for medical image segmentation as the first and …
images. They have been used extensively for medical image segmentation as the first and …
BIMCV COVID-19+: a large annotated dataset of RX and CT images from COVID-19 patients
MDLI Vayá, JM Saborit, JA Montell, A Pertusa… - arXiv preprint arXiv …, 2020 - arxiv.org
This paper describes BIMCV COVID-19+, a large dataset from the Valencian Region
Medical ImageBank (BIMCV) containing chest X-ray images CXR (CR, DX) and computed …
Medical ImageBank (BIMCV) containing chest X-ray images CXR (CR, DX) and computed …
Boosting COVID-19 image classification using MobileNetV3 and aquila optimizer algorithm
Currently, the world is still facing a COVID-19 (coronavirus disease 2019) classified as a
highly infectious disease due to its rapid spreading. The shortage of X-ray machines may …
highly infectious disease due to its rapid spreading. The shortage of X-ray machines may …
Transfer learning based novel ensemble classifier for COVID-19 detection from chest CT-scans
NS Shaik, TK Cherukuri - Computers in Biology and Medicine, 2022 - Elsevier
Abstract Coronavirus Disease 2019 (COVID-19) is a deadly infection that affects the
respiratory organs in humans as well as animals. By 2020, this disease turned out to be a …
respiratory organs in humans as well as animals. By 2020, this disease turned out to be a …
COVID‐19 deep learning prediction model using publicly available radiologist‐adjudicated chest x‐ray images as training data: preliminary findings
MZ Che Azemin, R Hassan… - International Journal …, 2020 - Wiley Online Library
The key component in deep learning research is the availability of training data sets. With a
limited number of publicly available COVID‐19 chest X‐ray images, the generalization and …
limited number of publicly available COVID‐19 chest X‐ray images, the generalization and …
POCOVID-Net: automatic detection of COVID-19 from a new lung ultrasound imaging dataset (POCUS)
With the rapid development of COVID-19 into a global pandemic, there is an ever more
urgent need for cheap, fast and reliable tools that can assist physicians in diagnosing …
urgent need for cheap, fast and reliable tools that can assist physicians in diagnosing …
Label-free segmentation of COVID-19 lesions in lung CT
Scarcity of annotated images hampers the building of automated solution for reliable COVID-
19 diagnosis and evaluation from CT. To alleviate the burden of data annotation, we herein …
19 diagnosis and evaluation from CT. To alleviate the burden of data annotation, we herein …
Improved manta ray foraging optimization for multi-level thresholding using COVID-19 CT images
EH Houssein, MM Emam, AA Ali - Neural Computing and Applications, 2021 - Springer
Abstract Coronavirus disease 2019 (COVID-19) is pervasive worldwide, posing a high risk to
people's safety and health. Many algorithms were developed to identify COVID-19. One way …
people's safety and health. Many algorithms were developed to identify COVID-19. One way …
COVID-19 case recognition from chest CT images by deep learning, entropy-controlled firefly optimization, and parallel feature fusion
In healthcare, a multitude of data is collected from medical sensors and devices, such as X-
ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that …
ray machines, magnetic resonance imaging, computed tomography (CT), and so on, that …