A review of medical image data augmentation techniques for deep learning applications

P Chlap, H Min, N Vandenberg… - Journal of Medical …, 2021 - Wiley Online Library
Research in artificial intelligence for radiology and radiotherapy has recently become
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …

Medical image segmentation using deep learning: A survey

R Wang, T Lei, R Cui, B Zhang, H Meng… - IET image …, 2022 - Wiley Online Library
Deep learning has been widely used for medical image segmentation and a large number of
papers has been presented recording the success of deep learning in the field. A …

Generative adversarial network in medical imaging: A review

X Yi, E Walia, P Babyn - Medical image analysis, 2019 - Elsevier
Generative adversarial networks have gained a lot of attention in the computer vision
community due to their capability of data generation without explicitly modelling the …

[HTML][HTML] Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward

E Elyan, P Vuttipittayamongkol, P Johnston… - Artificial Intelligence …, 2022 - oaepublish.com
The recent development in the areas of deep learning and deep convolutional neural
networks has significantly progressed and advanced the field of computer vision (CV) and …

Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge

AAA Setio, A Traverso, T De Bel, MSN Berens… - Medical image …, 2017 - Elsevier
Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has
been an active area of research for the last two decades. However, there have only been …

Application of deep learning techniques in diagnosis of covid-19 (coronavirus): a systematic review

YH Bhosale, KS Patnaik - Neural processing letters, 2023 - Springer
Covid-19 is now one of the most incredibly intense and severe illnesses of the twentieth
century. Covid-19 has already endangered the lives of millions of people worldwide due to …

xViTCOS: explainable vision transformer based COVID-19 screening using radiography

AK Mondal, A Bhattacharjee, P Singla… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Objective: Since its outbreak, the rapid spread of COrona VIrus Disease 2019 (COVID-19)
across the globe has pushed the health care system in many countries to the verge of …

Label-free segmentation of COVID-19 lesions in lung CT

Q Yao, L **ao, P Liu, SK Zhou - IEEE transactions on medical …, 2021 - ieeexplore.ieee.org
Scarcity of annotated images hampers the building of automated solution for reliable COVID-
19 diagnosis and evaluation from CT. To alleviate the burden of data annotation, we herein …

Fusing texture, shape and deep model-learned information at decision level for automated classification of lung nodules on chest CT

Y **e, J Zhang, Y **a, M Fulham, Y Zhang - Information Fusion, 2018 - Elsevier
The separation of malignant from benign lung nodules on chest computed tomography (CT)
is important for the early detection of lung cancer, since early detection and management …

[HTML][HTML] Computer-assisted decision support system in pulmonary cancer detection and stage classification on CT images

A Masood, B Sheng, P Li, X Hou, X Wei, J Qin… - Journal of biomedical …, 2018 - Elsevier
Pulmonary cancer is considered as one of the major causes of death worldwide. For the
detection of lung cancer, computer-assisted diagnosis (CADx) systems have been designed …