Recent advances and clinical applications of deep learning in medical image analysis
Deep learning has received extensive research interest in developing new medical image
processing algorithms, and deep learning based models have been remarkably successful …
processing algorithms, and deep learning based models have been remarkably successful …
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 …
Medical image segmentation review: The success of u-net
Automatic medical image segmentation is a crucial topic in the medical domain and
successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the …
successively a critical counterpart in the computer-aided diagnosis paradigm. U-Net is the …
Learning with limited annotations: a survey on deep semi-supervised learning for medical image segmentation
Medical image segmentation is a fundamental and critical step in many image-guided
clinical approaches. Recent success of deep learning-based segmentation methods usually …
clinical approaches. Recent success of deep learning-based segmentation methods usually …
Blockchain-federated-learning and deep learning models for covid-19 detection using ct imaging
With the increase of COVID-19 cases worldwide, an effective way is required to diagnose
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …
COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage …
Deep learning and medical image analysis for COVID-19 diagnosis and prediction
The coronavirus disease 2019 (COVID-19) pandemic has imposed dramatic challenges to
health-care organizations worldwide. To combat the global crisis, the use of thoracic …
health-care organizations worldwide. To combat the global crisis, the use of thoracic …
[HTML][HTML] Utilisation of deep learning for COVID-19 diagnosis
The COVID-19 pandemic that began in 2019 has resulted in millions of deaths worldwide.
Over this period, the economic and healthcare consequences of COVID-19 infection in …
Over this period, the economic and healthcare consequences of COVID-19 infection in …
Weakly supervised segmentation of COVID19 infection with scribble annotation on CT images
Segmentation of infections from CT scans is important for accurate diagnosis and follow-up
in tackling the COVID-19. Although the convolutional neural network has great potential to …
in tackling the COVID-19. Although the convolutional neural network has great potential 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 …
Synthetic data accelerates the development of generalizable learning-based algorithms for X-ray image analysis
Artificial intelligence (AI) now enables automated interpretation of medical images. However,
AI's potential use for interventional image analysis remains largely untapped. This is …
AI's potential use for interventional image analysis remains largely untapped. This is …