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 …
Graph-based deep learning for medical diagnosis and analysis: past, present and future
With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …
problems have been tackled. It has become critical to explore how machine learning and …
State-of-the-art deep learning in cardiovascular image analysis
Cardiovascular imaging is going to change substantially in the next decade, fueled by the
deep learning revolution. For medical professionals, it is important to keep track of these …
deep learning revolution. For medical professionals, it is important to keep track of these …
Blood vessel segmentation algorithms—review of methods, datasets and evaluation metrics
Background Blood vessel segmentation is a topic of high interest in medical image analysis
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
since the analysis of vessels is crucial for diagnosis, treatment planning and execution, and …
Why rankings of biomedical image analysis competitions should be interpreted with care
International challenges have become the standard for validation of biomedical image
analysis methods. Given their scientific impact, it is surprising that a critical analysis of …
analysis methods. Given their scientific impact, it is surprising that a critical analysis of …
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 in cardiology
P Bizopoulos, D Koutsouris - IEEE reviews in biomedical …, 2018 - ieeexplore.ieee.org
The medical field is creating large amount of data that physicians are unable to decipher
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review
In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …
mortality globally. At early stages, CVDs appear with minor symptoms and progressively get …
[HTML][HTML] Automated segmentation of normal and diseased coronary arteries–the asoca challenge
R Gharleghi, D Adikari, K Ellenberger, SY Ooi… - … Medical Imaging and …, 2022 - Elsevier
Cardiovascular disease is a major cause of death worldwide. Computed Tomography
Coronary Angiography (CTCA) is a non-invasive method used to evaluate coronary artery …
Coronary Angiography (CTCA) is a non-invasive method used to evaluate coronary artery …
Learning physical properties in complex visual scenes: An intelligent machine for perceiving blood flow dynamics from static CT angiography imaging
Humans perceive physical properties such as motion and elastic force by observing objects
in visual scenes. Recent research has proven that computers are capable of inferring …
in visual scenes. Recent research has proven that computers are capable of inferring …