A deep learning-based integrated framework for quality-aware undersampled cine cardiac MRI reconstruction and analysis
Cine cardiac magnetic resonance (CMR) imaging is considered the gold standard for
cardiac function evaluation. However, cine CMR acquisition is inherently slow and in recent …
cardiac function evaluation. However, cine CMR acquisition is inherently slow and in recent …
Quality-aware cine cardiac MRI reconstruction and analysis from undersampled k-space data
Cine cardiac MRI is routinely acquired for the assessment of cardiac health, but the imaging
process is slow and typically requires several breath-holds to acquire sufficient k-space …
process is slow and typically requires several breath-holds to acquire sufficient k-space …
CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI
Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for
cardiac diseases. However, a significant drawback of CMR is its slow imaging speed …
cardiac diseases. However, a significant drawback of CMR is its slow imaging speed …
Accelerating Cardiac MRI Reconstruction with CMRatt: An Attention-Driven Approach
A Hashmi, J Dietlmeier, KM Curran… - arXiv preprint arXiv …, 2024 - arxiv.org
Cine cardiac magnetic resonance (CMR) imaging is recognised as the benchmark modality
for the comprehensive assessment of cardiac function. Nevertheless, the acquisition process …
for the comprehensive assessment of cardiac function. Nevertheless, the acquisition process …
Inline AI: Open-source Deep Learning Inference for Cardiac MR
Cardiac Magnetic Resonance (CMR) is established as a non-invasive imaging technique for
evaluation of heart function, anatomy, and myocardial tissue characterization. Quantitative …
evaluation of heart function, anatomy, and myocardial tissue characterization. Quantitative …
Spatio-temporal deep learning-based undersampling artefact reduction for 2D radial cine MRI with limited training data
In this work we reduce undersampling artefacts in two-dimensional (2D) golden-angle radial
cine cardiac MRI by applying a modified version of the U-net. The network is trained on 2D …
cine cardiac MRI by applying a modified version of the U-net. The network is trained on 2D …
CMRxRecon2024: A Multi-Modality, Multi-View K-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI
Cardiac magnetic resonance imaging (MRI) has emerged as a clinically gold-standard
technique for diagnosing cardiac diseases, thanks to its ability to provide diverse information …
technique for diagnosing cardiac diseases, thanks to its ability to provide diverse information …
Unsupervised reconstruction of accelerated cardiac cine MRI using Neural Fields
Cardiac cine MRI is the gold standard for cardiac functional assessment, but the inherently
slow acquisition process creates the necessity of reconstruction approaches for accelerated …
slow acquisition process creates the necessity of reconstruction approaches for accelerated …
[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 …
[HTML][HTML] Super-resolution of cardiac MR cine imaging using conditional GANs and unsupervised transfer learning
Y Xia, N Ravikumar, JP Greenwood, S Neubauer… - Medical Image …, 2021 - Elsevier
Abstract High-resolution (HR), isotropic cardiac Magnetic Resonance (MR) cine imaging is
challenging since it requires long acquisition and patient breath-hold times. Instead, 2D …
challenging since it requires long acquisition and patient breath-hold times. Instead, 2D …