A review of medical image data augmentation techniques for deep learning applications
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 …
increasingly reliant on the use of deep learning‐based algorithms. While the performance of …
AI-based reconstruction for fast MRI—A systematic review and meta-analysis
Compressed sensing (CS) has been playing a key role in accelerating the magnetic
resonance imaging (MRI) acquisition process. With the resurgence of artificial intelligence …
resonance imaging (MRI) acquisition process. With the resurgence of artificial intelligence …
[HTML][HTML] Clinical quantitative cardiac imaging for the assessment of myocardial ischaemia
Cardiac imaging has a pivotal role in the prevention, diagnosis and treatment of ischaemic
heart disease. SPECT is most commonly used for clinical myocardial perfusion imaging …
heart disease. SPECT is most commonly used for clinical myocardial perfusion imaging …
Deep learning applications in magnetic resonance imaging: has the future become present?
Deep learning technologies and applications demonstrate one of the most important
upcoming developments in radiology. The impact and influence of these technologies on …
upcoming developments in radiology. The impact and influence of these technologies on …
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] From compressed-sensing to artificial intelligence-based cardiac MRI reconstruction
Cardiac magnetic resonance (CMR) imaging is an important tool for the non-invasive
assessment of cardiovascular disease. However, CMR suffers from long acquisition times …
assessment of cardiovascular disease. However, CMR suffers from long acquisition times …
Cardiac MR: from theory to practice
Cardiovascular disease (CVD) is the leading single cause of morbidity and mortality,
causing over 17. 9 million deaths worldwide per year with associated costs of over $800 …
causing over 17. 9 million deaths worldwide per year with associated costs of over $800 …
Deep‐learning based super‐resolution for 3D isotropic coronary MR angiography in less than a minute
Purpose To develop and evaluate a novel and generalizable super‐resolution (SR) deep‐
learning framework for motion‐compensated isotropic 3D coronary MR angiography …
learning framework for motion‐compensated isotropic 3D coronary MR angiography …
Machine learning in magnetic resonance imaging: image reconstruction
Abstract Magnetic Resonance Imaging (MRI) plays a vital role in diagnosis, management
and monitoring of many diseases. However, it is an inherently slow imaging technique. Over …
and monitoring of many diseases. However, it is an inherently slow imaging technique. Over …
Cine cardiac MRI motion artifact reduction using a recurrent neural network
Cine cardiac magnetic resonance imaging (MRI) is widely used for the diagnosis of cardiac
diseases thanks to its ability to present cardiovascular features in excellent contrast. As …
diseases thanks to its ability to present cardiovascular features in excellent contrast. As …