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Recent advances and clinical applications of deep learning in medical image analysis
Deep learning has received extensive research interest in develo** 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 …
[HTML][HTML] 3D deep learning on medical images: a review
The rapid advancements in machine learning, graphics processing technologies and the
availability of medical imaging data have led to a rapid increase in the use of deep learning …
availability of medical imaging data have led to a rapid increase in the use of deep learning …
Application of deep learning technique to manage COVID-19 in routine clinical practice using CT images: Results of 10 convolutional neural networks
Fast diagnostic methods can control and prevent the spread of pandemic diseases like
coronavirus disease 2019 (COVID-19) and assist physicians to better manage patients in …
coronavirus disease 2019 (COVID-19) and assist physicians to better manage patients in …
Transfer learning with deep convolutional neural network (CNN) for pneumonia detection using chest X-ray
Pneumonia is a life-threatening disease, which occurs in the lungs caused by either
bacterial or viral infection. It can be life-endangering if not acted upon at the right time and …
bacterial or viral infection. It can be life-endangering if not acted upon at the right time and …
A novel transfer learning based approach for pneumonia detection in chest X-ray images
Pneumonia is among the top diseases which cause most of the deaths all over the world.
Virus, bacteria and fungi can all cause pneumonia. However, it is difficult to judge the …
Virus, bacteria and fungi can all cause pneumonia. However, it is difficult to judge the …
Brain tumor classification using deep CNN features via transfer learning
Brain tumor classification is an important problem in computer-aided diagnosis (CAD) for
medical applications. This paper focuses on a 3-class classification problem to differentiate …
medical applications. This paper focuses on a 3-class classification problem to differentiate …
Convolutional neural networks for medical image analysis: state-of-the-art, comparisons, improvement and perspectives
Convolutional neural networks, are one of the most representative deep learning models.
CNNs were extensively used in many aspects of medical image analysis, allowing for great …
CNNs were extensively used in many aspects of medical image analysis, allowing for great …
Medical imaging and nuclear medicine: a Lancet Oncology Commission
The diagnosis and treatment of patients with cancer requires access to imaging to ensure
accurate management decisions and optimal outcomes. Our global assessment of imaging …
accurate management decisions and optimal outcomes. Our global assessment of imaging …
Deep CNN for brain tumor classification
Brain tumor represents one of the most fatal cancers around the world. It is common cancer
in adults and children. It has the lowest survival rate and various types depending on their …
in adults and children. It has the lowest survival rate and various types depending on their …
A deep learning model based on concatenation approach for the diagnosis of brain tumor
Brain tumor is a deadly disease and its classification is a challenging task for radiologists
because of the heterogeneous nature of the tumor cells. Recently, computer-aided …
because of the heterogeneous nature of the tumor cells. Recently, computer-aided …