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 …
Deep learning for cardiac image segmentation: a review
Deep learning has become the most widely used approach for cardiac image segmentation
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
in recent years. In this paper, we provide a review of over 100 cardiac image segmentation …
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 …
A recurrent CNN for automatic detection and classification of coronary artery plaque and stenosis in coronary CT angiography
M Zreik, RW Van Hamersvelt… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Various types of atherosclerotic plaque and varying grades of stenosis could lead to different
management of patients with a coronary artery disease. Therefore, it is crucial to detect and …
management of patients with a coronary artery disease. Therefore, it is crucial to detect and …
Deep learning-based regression and classification for automatic landmark localization in medical images
In this study, we propose a fast and accurate method to automatically localize anatomical
landmarks in medical images. We employ a global-to-local localization approach using fully …
landmarks in medical images. We employ a global-to-local localization approach using fully …
Review of ECG detection and classification based on deep learning: Coherent taxonomy, motivation, open challenges and recommendations
An electrocardiogram (ECG) is one of the most promising approaches used for the detection
and classification of cardiovascular diseases (CVDs) in recent years. This work reviewed …
and classification of cardiovascular diseases (CVDs) in recent years. This work reviewed …
Anatomy-aided deep learning for medical image segmentation: a review
Deep learning (DL) has become widely used for medical image segmentation in recent
years. However, despite these advances, there are still problems for which DL-based …
years. However, despite these advances, there are still problems for which DL-based …
Research progress of machine learning and deep learning in intelligent diagnosis of the coronary atherosclerotic heart disease
H Lu, Y Yao, L Wang, J Yan, S Tu… - … Methods in Medicine, 2022 - Wiley Online Library
The coronary atherosclerotic heart disease is a common cardiovascular disease with high
morbidity, disability, and societal burden. Early, precise, and comprehensive diagnosis of …
morbidity, disability, and societal burden. Early, precise, and comprehensive diagnosis of …
Advanced atherosclerosis imaging by CT: radiomics, machine learning and deep learning
M Kolossváry, CN De Cecco, G Feuchtner… - Journal of …, 2019 - Elsevier
In the last decade, technical advances in the field of medical imaging significantly improved
and broadened the application of coronary CT angiography (CCTA) for the non-invasive …
and broadened the application of coronary CT angiography (CCTA) for the non-invasive …
Value creation through artificial intelligence and cardiovascular imaging: a scientific statement from the American Heart Association
Multiple applications for machine learning and artificial intelligence (AI) in cardiovascular
imaging are being proposed and developed. However, the processes involved in …
imaging are being proposed and developed. However, the processes involved in …