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 …
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 …
Review and prospect: artificial intelligence in advanced medical imaging
Artificial intelligence (AI) as an emerging technology is gaining momentum in medical
imaging. Recently, deep learning-based AI techniques have been actively investigated in …
imaging. Recently, deep learning-based AI techniques have been actively investigated in …
Deep learning for fast MR imaging: A review for learning reconstruction from incomplete k-space data
Magnetic resonance imaging is a powerful imaging modality that can provide versatile
information. However, it has a fundamental challenge that is time consuming to acquire …
information. However, it has a fundamental challenge that is time consuming to acquire …
Analysis of deep complex‐valued convolutional neural networks for MRI reconstruction and phase‐focused applications
Purpose Deep learning has had success with MRI reconstruction, but previously published
works use real‐valued networks. The few works which have tried complex‐valued networks …
works use real‐valued networks. The few works which have tried complex‐valued networks …
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 …
Present and future innovations in AI and cardiac MRI
MA Morales, WJ Manning, R Nezafat - Radiology, 2024 - pubs.rsna.org
Cardiac MRI is used to diagnose and treat patients with a multitude of cardiovascular
diseases. Despite the growth of clinical cardiac MRI, complicated image prescriptions and …
diseases. Despite the growth of clinical cardiac MRI, complicated image prescriptions and …
Deep learning-based reconstruction for cardiac MRI: a review
Cardiac magnetic resonance (CMR) is an essential clinical tool for the assessment of
cardiovascular disease. Deep learning (DL) has recently revolutionized the field through …
cardiovascular disease. Deep learning (DL) has recently revolutionized the field through …
Progressively volumetrized deep generative models for data-efficient contextual learning of MR image recovery
Magnetic resonance imaging (MRI) offers the flexibility to image a given anatomic volume
under a multitude of tissue contrasts. Yet, scan time considerations put stringent limits on the …
under a multitude of tissue contrasts. Yet, scan time considerations put stringent limits on the …
Multi‐domain convolutional neural network (MD‐CNN) for radial reconstruction of dynamic cardiac MRI
H El‐Rewaidy, AS Fahmy… - Magnetic …, 2021 - Wiley Online Library
Purpose Cardiac MR cine imaging allows accurate and reproducible assessment of cardiac
function. However, its long scan time not only limits the spatial and temporal resolutions but …
function. However, its long scan time not only limits the spatial and temporal resolutions but …