Guest editorial deep learning in medical imaging: Overview and future promise of an exciting new technique
H Greenspan, B Van Ginneken… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
The papers in this special section focus on the technology and applications supported by
deep learning. Deep learning is a growing trend in general data analysis and has been …
deep learning. Deep learning is a growing trend in general data analysis and has been …
A review on deep learning techniques for the diagnosis of novel coronavirus (COVID-19)
Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation all over the world
and has become one of the most acute and severe ailments in the past hundred years. The …
and has become one of the most acute and severe ailments in the past hundred years. The …
Development and evaluation of an artificial intelligence system for COVID-19 diagnosis
Early detection of COVID-19 based on chest CT enables timely treatment of patients and
helps control the spread of the disease. We proposed an artificial intelligence (AI) system for …
helps control the spread of the disease. We proposed an artificial intelligence (AI) system for …
Interstitial lung abnormalities detected incidentally on CT: a Position Paper from the Fleischner Society
H Hatabu, GM Hunninghake, L Richeldi… - The lancet Respiratory …, 2020 - thelancet.com
The term interstitial lung abnormalities refers to specific CT findings that are potentially
compatible with interstitial lung disease in patients without clinical suspicion of the disease …
compatible with interstitial lung disease in patients without clinical suspicion of the disease …
Deep convolutional neural networks for computer-aided detection: CNN architectures, dataset characteristics and transfer learning
Remarkable progress has been made in image recognition, primarily due to the availability
of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs …
of large-scale annotated datasets and deep convolutional neural networks (CNNs). CNNs …
Lung pattern classification for interstitial lung diseases using a deep convolutional neural network
M Anthimopoulos, S Christodoulidis… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Automated tissue characterization is one of the most crucial components of a computer
aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research …
aided diagnosis (CAD) system for interstitial lung diseases (ILDs). Although much research …
Review on Diagnosis of COVID‐19 from Chest CT Images Using Artificial Intelligence
The COVID‐19 diagnostic approach is mainly divided into two broad categories, a
laboratory‐based and chest radiography approach. The last few months have witnessed a …
laboratory‐based and chest radiography approach. The last few months have witnessed a …
Going deep in medical image analysis: concepts, methods, challenges, and future directions
Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …
technology has recently attracted so much interest of the Medical Imaging Community that it …
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 …
Medical image classification with convolutional neural network
Image patch classification is an important task in many different medical imaging
applications. In this work, we have designed a customized Convolutional Neural Networks …
applications. In this work, we have designed a customized Convolutional Neural Networks …