Rapid MR relaxometry using deep learning: An overview of current techniques and emerging trends
Quantitative mapping of MR tissue parameters such as the spin‐lattice relaxation time (T1),
the spin‐spin relaxation time (T2), and the spin‐lattice relaxation in the rotating frame (T1ρ) …
the spin‐spin relaxation time (T2), and the spin‐lattice relaxation in the rotating frame (T1ρ) …
Magnetic resonance fingerprinting review part 2: Technique and directions
Magnetic resonance fingerprinting (MRF) is a general framework to quantify multiple MR‐
sensitive tissue properties with a single acquisition. There have been numerous advances in …
sensitive tissue properties with a single acquisition. There have been numerous advances in …
Image reconstruction: From sparsity to data-adaptive methods and machine learning
The field of medical image reconstruction has seen roughly four types of methods. The first
type tended to be analytical methods, such as filtered backprojection (FBP) for X-ray …
type tended to be analytical methods, such as filtered backprojection (FBP) for X-ray …
Low rank alternating direction method of multipliers reconstruction for MR fingerprinting
Purpose The proposed reconstruction framework addresses the reconstruction accuracy,
noise propagation and computation time for magnetic resonance fingerprinting. Methods …
noise propagation and computation time for magnetic resonance fingerprinting. Methods …
Improved magnetic resonance fingerprinting reconstruction with low‐rank and subspace modeling
B Zhao, K Setsompop, E Adalsteinsson… - Magnetic resonance …, 2018 - Wiley Online Library
Purpose This article introduces a constrained imaging method based on low‐rank and
subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). Theory …
subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). Theory …
Deep learning for fast and spatially constrained tissue quantification from highly accelerated data in magnetic resonance fingerprinting
Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that can
simultaneously measure multiple important tissue properties of human body. Although MRF …
simultaneously measure multiple important tissue properties of human body. Although MRF …
3D MR fingerprinting with accelerated stack-of-spirals and hybrid sliding-window and GRAPPA reconstruction
Purpose Whole-brain high-resolution quantitative imaging is extremely encoding intensive,
and its rapid and robust acquisition remains a challenge. Here we present a 3D MR …
and its rapid and robust acquisition remains a challenge. Here we present a 3D MR …
Automated design of pulse sequences for magnetic resonance fingerprinting using physics-inspired optimization
SP Jordan, S Hu, I Rozada… - Proceedings of the …, 2021 - National Acad Sciences
Magnetic resonance fingerprinting (MRF) is a method to extract quantitative tissue properties
such as T 1 and T 2 relaxation rates from arbitrary pulse sequences using conventional MRI …
such as T 1 and T 2 relaxation rates from arbitrary pulse sequences using conventional MRI …
Coupled dictionary learning for multi-contrast MRI reconstruction
Magnetic resonance (MR) imaging tasks often involve multiple contrasts, such as T1-
weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR) data. These …
weighted, T2-weighted and fluid-attenuated inversion recovery (FLAIR) data. These …
Sparsity and locally low rank regularization for MR fingerprinting
Purpose Develop a sparse and locally low rank (LLR) regularized reconstruction to
accelerate MR fingerprinting (MRF). Methods Recent works have introduced low rank …
accelerate MR fingerprinting (MRF). Methods Recent works have introduced low rank …