U-net and its variants for medical image segmentation: A review of theory and applications
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …
tasks. These traits provide U-net with a high utility within the medical imaging community …
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
In the last few years, the deep learning (DL) computing paradigm has been deemed the
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
Gold Standard in the machine learning (ML) community. Moreover, it has gradually become …
COVID-19 lung CT image segmentation using deep learning methods: U-Net versus SegNet
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 …
COVID-19 patients. In this paper, we present feasible solutions for detecting and labeling …
AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system
The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic
burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to …
burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to …
Automated detection and forecasting of covid-19 using deep learning techniques: A review
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 …
epidemic, caused by the SARS-CoV-2 virus. Initially, COVID-19 was diagnosed using real …
Automatic COVID-19 detection from X-ray images using ensemble learning with convolutional neural network
COVID-19 continues to have catastrophic effects on the lives of human beings throughout
the world. To combat this disease it is necessary to screen the affected patients in a fast and …
the world. To combat this disease it is necessary to screen the affected patients in a fast and …
Modality specific U-Net variants for biomedical image segmentation: a survey
With the advent of advancements in deep learning approaches, such as deep convolution
neural network, residual neural network, adversarial network; U-Net architectures are most …
neural network, residual neural network, adversarial network; U-Net architectures are most …
Ms RED: A novel multi-scale residual encoding and decoding network for skin lesion segmentation
Abstract Computer-Aided Diagnosis (CAD) for dermatological diseases offers one of the
most notable showcases where deep learning technologies display their impressive …
most notable showcases where deep learning technologies display their impressive …
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 …
(SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of …
[HTML][HTML] Transfer learning with fine-tuned deep CNN ResNet50 model for classifying COVID-19 from chest X-ray images
COVID-19 cases are putting pressure on healthcare systems all around the world. Due to
the lack of available testing kits, it is impractical for screening every patient with a respiratory …
the lack of available testing kits, it is impractical for screening every patient with a respiratory …