[HTML][HTML] A review and experimental evaluation of deep learning methods for MRI reconstruction
Following the success of deep learning in a wide range of applications, neural network-
based machine-learning techniques have received significant interest for accelerating …
based machine-learning techniques have received significant interest for accelerating …
Sparse reconstruction techniques in magnetic resonance imaging: methods, applications, and challenges to clinical adoption
AC Yang, M Kretzler, S Sudarski, V Gulani… - Investigative …, 2016 - journals.lww.com
The family of sparse reconstruction techniques, including the recently introduced
compressed sensing framework, has been extensively explored to reduce scan times in …
compressed sensing framework, has been extensively explored to reduce scan times in …
Maximum likelihood reconstruction for magnetic resonance fingerprinting
B Zhao, K Setsompop, H Ye… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
This paper introduces a statistical estimation framework for magnetic resonance (MR)
fingerprinting, a recently proposed quantitative imaging paradigm. Within this framework, we …
fingerprinting, a recently proposed quantitative imaging paradigm. Within this framework, we …
Accelerated T2 mapping combining parallel MRI and model‐based reconstruction: GRAPPATINI
Background Quantitative T2 measurements are sensitive to intra‐and extracellular water
accumulation and myelin loss. Therefore, quantitative T2 promises to be a good biomarker …
accumulation and myelin loss. Therefore, quantitative T2 promises to be a good biomarker …
A compressed sensing framework for magnetic resonance fingerprinting
Inspired by the recently proposed magnetic resonance fingerprinting (MRF) technique, we
develop a principled compressed sensing framework for quantitative MRI. The three key …
develop a principled compressed sensing framework for quantitative MRI. The three key …
Model‐based T1 mapping with sparsity constraints using single‐shot inversion‐recovery radial FLASH
Purpose To develop a model‐based reconstruction technique for single‐shot T1 mapping
with high spatial resolution, accuracy, and precision using an inversion‐recovery (IR) fast …
with high spatial resolution, accuracy, and precision using an inversion‐recovery (IR) fast …
Physics-based reconstruction methods for magnetic resonance imaging
Conventional magnetic resonance imaging (MRI) is hampered by long scan times and only
qualitative image contrasts that prohibit a direct comparison between different systems. To …
qualitative image contrasts that prohibit a direct comparison between different systems. To …
Rapid T1 quantification from high resolution 3D data with model‐based reconstruction
Purpose Magnetic resonance imaging protocols for the assessment of quantitative
information suffer from long acquisition times since multiple measurements in a parametric …
information suffer from long acquisition times since multiple measurements in a parametric …
Optimization and validation of accelerated golden‐angle radial sparse MRI reconstruction with self‐calibrating GRAPPA operator gridding
Purpose Golden‐angle radial sparse parallel (GRASP) MRI reconstruction requires gridding
and regridding to transform data between radial and Cartesian k‐space. These operations …
and regridding to transform data between radial and Cartesian k‐space. These operations …
Latest advances in image acceleration: all dimensions are fair game
Magnetic resonance imaging (MRI) is a versatile modality that can generate high‐resolution
images with a variety of tissue contrasts. However, MRI is a slow technique and requires …
images with a variety of tissue contrasts. However, MRI is a slow technique and requires …