AI in medical imaging informatics: current challenges and future directions
This paper reviews state-of-the-art research solutions across the spectrum of medical
imaging informatics, discusses clinical translation, and provides future directions for …
imaging informatics, discusses clinical translation, and provides future directions for …
MRI-guided radiation therapy: an emerging paradigm in adaptive radiation oncology
Radiation therapy (RT) continues to be one of the mainstays of cancer treatment.
Considerable efforts have been recently devoted to integrating MRI into clinical RT planning …
Considerable efforts have been recently devoted to integrating MRI into clinical RT planning …
KIKI‐net: cross‐domain convolutional neural networks for reconstructing undersampled magnetic resonance images
Purpose To demonstrate accurate MR image reconstruction from undersampled k‐space
data using cross‐domain convolutional neural networks (CNNs) Methods Cross‐domain …
data using cross‐domain convolutional neural networks (CNNs) Methods Cross‐domain …
Self‐supervised learning of physics‐guided reconstruction neural networks without fully sampled reference data
B Yaman, SAH Hosseini, S Moeller… - Magnetic resonance …, 2020 - Wiley Online Library
Purpose To develop a strategy for training a physics‐guided MRI reconstruction neural
network without a database of fully sampled data sets. Methods Self‐supervised learning via …
network without a database of fully sampled data sets. Methods Self‐supervised learning via …
XD‐GRASP: golden‐angle radial MRI with reconstruction of extra motion‐state dimensions using compressed sensing
Purpose To develop a novel framework for free‐breathing MRI called XD‐GRASP, which
sorts dynamic data into extra motion‐state dimensions using the self‐navigation properties …
sorts dynamic data into extra motion‐state dimensions using the self‐navigation properties …
On the applications of robust PCA in image and video processing
Robust principal component analysis (RPCA) via decomposition into low-rank plus sparse
matrices offers a powerful framework for a large variety of applications such as image …
matrices offers a powerful framework for a large variety of applications such as image …
Golden‐angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden‐angle radial sampling for fast and flexible dynamic …
Purpose To develop a fast and flexible free‐breathing dynamic volumetric MRI technique,
iterative Golden‐angle RAdial Sparse Parallel MRI (iGRASP), that combines compressed …
iterative Golden‐angle RAdial Sparse Parallel MRI (iGRASP), that combines compressed …
Low‐rank plus sparse matrix decomposition for accelerated dynamic MRI with separation of background and dynamic components
Purpose To apply the low‐rank plus sparse (L+ S) matrix decomposition model to
reconstruct undersampled dynamic MRI as a superposition of background and dynamic …
reconstruct undersampled dynamic MRI as a superposition of background and dynamic …
[HTML][HTML] Machine learning in cardiovascular magnetic resonance: basic concepts and applications
Abstract Machine learning (ML) is making a dramatic impact on cardiovascular magnetic
resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR …
resonance (CMR) in many ways. This review seeks to highlight the major areas in CMR …
Compressed sensing for body MRI
The introduction of compressed sensing for increasing imaging speed in magnetic
resonance imaging (MRI) has raised significant interest among researchers and clinicians …
resonance imaging (MRI) has raised significant interest among researchers and clinicians …