Integrated MRI-guided radiotherapy—opportunities and challenges
MRI can help to categorize tissues as malignant or non-malignant both anatomically and
functionally, with a high level of spatial and temporal resolution. This non-invasive imaging …
functionally, with a high level of spatial and temporal resolution. This non-invasive imaging …
The future of MRI in radiation therapy: Challenges and opportunities for the MR community
RJ Goodburn, MEP Philippens… - Magnetic resonance …, 2022 - Wiley Online Library
Radiation therapy is a major component of cancer treatment pathways worldwide. The main
aim of this treatment is to achieve tumor control through the delivery of ionizing radiation …
aim of this treatment is to achieve tumor control through the delivery of ionizing radiation …
One-dimensional deep low-rank and sparse network for accelerated MRI
Deep learning has shown astonishing performance in accelerated magnetic resonance
imaging (MRI). Most state-of-the-art deep learning reconstructions adopt the powerful …
imaging (MRI). Most state-of-the-art deep learning reconstructions adopt the powerful …
Movienet: Deep space–time‐coil reconstruction network without k‐space data consistency for fast motion‐resolved 4D MRI
Purpose To develop a novel deep learning approach for 4D‐MRI reconstruction, named
Movienet, which exploits space–time‐coil correlations and motion preservation instead of k …
Movienet, which exploits space–time‐coil correlations and motion preservation instead of k …
Accelerated respiratory‐resolved 4D‐MRI with separable spatio‐temporal neural networks
Background Respiratory‐resolved four‐dimensional magnetic resonance imaging (4D‐MRI)
provides essential motion information for accurate radiation treatments of mobile tumors …
provides essential motion information for accurate radiation treatments of mobile tumors …
GRASPNET: fast spatiotemporal deep learning reconstruction of golden‐angle radial data for free‐breathing dynamic contrast‐enhanced magnetic resonance …
R Jafari, RKG Do, MD LaGratta, M Fung… - NMR in …, 2023 - Wiley Online Library
The purpose of the current study was to develop a deep learning technique called Golden‐
angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic …
angle RAdial Sparse Parallel Network (GRASPnet) for fast reconstruction of dynamic …
Distortion‐corrected image reconstruction with deep learning on an MRI‐Linac
Purpose MRI is increasingly utilized for image‐guided radiotherapy due to its outstanding
soft‐tissue contrast and lack of ionizing radiation. However, geometric distortions caused by …
soft‐tissue contrast and lack of ionizing radiation. However, geometric distortions caused by …
Real-time 4D MRI using MR signature matching (MRSIGMA) on a 1.5 T MR-Linac system
Objective. To develop real-time 4D MRI using MR signature matching (MRSIGMA) for
volumetric motion imaging in patients with pancreatic cancer on a 1.5 T MR-Linac system …
volumetric motion imaging in patients with pancreatic cancer on a 1.5 T MR-Linac system …
[HTML][HTML] Accelerating 4D image reconstruction for magnetic resonance-guided radiotherapy
Background and purpose Physiological motion impacts the dose delivered to tumours and
vital organs in external beam radiotherapy and particularly in particle therapy. The excellent …
vital organs in external beam radiotherapy and particularly in particle therapy. The excellent …
Uncertainty‐aware physics‐driven deep learning network for free‐breathing liver fat and R2* quantification using self‐gated stack‐of‐radial MRI
Purpose To develop a deep learning‐based method for rapid liver proton‐density fat fraction
(PDFF) and R2* quantification with built‐in uncertainty estimation using self‐gated free …
(PDFF) and R2* quantification with built‐in uncertainty estimation using self‐gated free …