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 …
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
SK Zhou, H Greenspan, C Davatzikos… - Proceedings of the …, 2021 - ieeexplore.ieee.org
Since its renaissance, deep learning has been widely used in various medical imaging tasks
and has achieved remarkable success in many medical imaging applications, thereby …
and has achieved remarkable success in many medical imaging applications, thereby …
Covidgan: data augmentation using auxiliary classifier gan for improved covid-19 detection
Coronavirus (COVID-19) is a viral disease caused by severe acute respiratory syndrome
coronavirus 2 (SARS-CoV-2). The spread of COVID-19 seems to have a detrimental effect …
coronavirus 2 (SARS-CoV-2). The spread of COVID-19 seems to have a detrimental effect …
Designing deep learning studies in cancer diagnostics
A Kleppe, OJ Skrede, S De Raedt, K Liestøl… - Nature Reviews …, 2021 - nature.com
The number of publications on deep learning for cancer diagnostics is rapidly increasing,
and systems are frequently claimed to perform comparable with or better than clinicians …
and systems are frequently claimed to perform comparable with or better than clinicians …
Literature review: Efficient deep neural networks techniques for medical image analysis
MA Abdou - Neural Computing and Applications, 2022 - Springer
Significant evolution in deep learning took place in 2010, when software developers started
using graphical processing units for general-purpose applications. From that date, the deep …
using graphical processing units for general-purpose applications. From that date, the deep …
[HTML][HTML] Recent advancement in cancer detection using machine learning: Systematic survey of decades, comparisons and challenges
T Saba - Journal of infection and public health, 2020 - Elsevier
Cancer is a fatal illness often caused by genetic disorder aggregation and a variety of
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
pathological changes. Cancerous cells are abnormal areas often growing in any part of …
Deep learning in medical imaging and radiation therapy
The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification
M Frid-Adar, I Diamant, E Klang, M Amitai… - Neurocomputing, 2018 - Elsevier
Deep learning methods, and in particular convolutional neural networks (CNNs), have led to
an enormous breakthrough in a wide range of computer vision tasks, primarily by using …
an enormous breakthrough in a wide range of computer vision tasks, primarily by using …
Deep learning applications in medical image analysis
The tremendous success of machine learning algorithms at image recognition tasks in
recent years intersects with a time of dramatically increased use of electronic medical …
recent years intersects with a time of dramatically increased use of electronic medical …
Deep learning: a primer for radiologists
Deep learning is a class of machine learning methods that are gaining success and
attracting interest in many domains, including computer vision, speech recognition, natural …
attracting interest in many domains, including computer vision, speech recognition, natural …