[HTML][HTML] The Future of CMR: All-in-One vs. Real-Time CMR (Part 1)
AG Christodoulou, G Cruz, A Arami… - Journal of …, 2024 - Elsevier
ABSTRACT Cardiac Magnetic Resonance (CMR) protocols can be lengthy and complex,
which has driven the research community to develop new technologies to make these …
which has driven the research community to develop new technologies to make these …
Simultaneous multi-parametric acquisition and reconstruction techniques in cardiac magnetic resonance imaging: Basic concepts and status of clinical development
Simultaneous multi-parametric acquisition and reconstruction techniques (SMART) are
gaining attention for their potential to overcome some of cardiovascular magnetic resonance …
gaining attention for their potential to overcome some of cardiovascular magnetic resonance …
Deep learning reconstruction for cardiac magnetic resonance fingerprinting T1 and T2 mapping
Purpose To develop a deep learning method for rapidly reconstructing T1 and T2 maps from
undersampled electrocardiogram (ECG) triggered cardiac magnetic resonance …
undersampled electrocardiogram (ECG) triggered cardiac magnetic resonance …
[HTML][HTML] Accelerated cardiac T1 mapping in four heartbeats with inline MyoMapNet: a deep learning-based T1 estimation approach
Purpose To develop and evaluate MyoMapNet, a rapid myocardial T 1 mapping approach
that uses fully connected neural networks (FCNN) to estimate T 1 values from four T 1 …
that uses fully connected neural networks (FCNN) to estimate T 1 values from four T 1 …
DeepFittingNet: A deep neural network‐based approach for simplifying cardiac T1 and T2 estimation with improved robustness
R Guo, D Si, Y Fan, X Qian, H Zhang… - Magnetic …, 2023 - Wiley Online Library
Purpose To develop and evaluate a deep neural network (DeepFittingNet) for T1/T2
estimation of the most commonly used cardiovascular MR mapping sequences to simplify …
estimation of the most commonly used cardiovascular MR mapping sequences to simplify …
Roadmap on signal processing for next generation measurement systems
Signal processing is a fundamental component of almost any sensor-enabled system, with a
wide range of applications across different scientific disciplines. Time series data, images …
wide range of applications across different scientific disciplines. Time series data, images …
Scanner‐Independent MyoMapNet for Accelerated Cardiac MRI T1 Mapping Across Vendors and Field Strengths
Background In cardiac T1 mapping, a series of T1‐weighted (T1w) images are collected and
numerically fitted to a two or three‐parameter model of the signal recovery to estimate voxel …
numerically fitted to a two or three‐parameter model of the signal recovery to estimate voxel …
Deep learning–enhanced T1 mapping with spatial‐temporal and physical constraint
Purpose To propose a reconstruction framework to generate accurate T1 maps for a fast MR
T1 mapping sequence. Methods A deep learning–enhanced T1 mapping method with …
T1 mapping sequence. Methods A deep learning–enhanced T1 mapping method with …
Impact of deep learning architectures on accelerated cardiac T1 mapping using MyoMapNet
The objective of the current study was to investigate the performance of various deep
learning (DL) architectures for MyoMapNet, a DL model for T1 estimation using accelerated …
learning (DL) architectures for MyoMapNet, a DL model for T1 estimation using accelerated …
Motion correction for native myocardial T1 mapping using self‐supervised deep learning registration with contrast separation
In myocardial T1 mapping, undesirable motion poses significant challenges because
uncorrected motion can affect T1 estimation accuracy and cause incorrect diagnosis. In this …
uncorrected motion can affect T1 estimation accuracy and cause incorrect diagnosis. In this …