Intrafraction motion management with MR-guided radiation therapy

MF Fast, M Cao, P Parikh, JJ Sonke - Seminars in radiation oncology, 2024 - Elsevier
High quality radiation therapy requires highly accurate and precise dose delivery. MR-
guided radiotherapy (MRgRT), integrating an MRI scanner with a linear accelerator, offers …

Stop moving: MR motion correction as an opportunity for artificial intelligence

Z Zhou, P Hu, H Qi - Magnetic Resonance Materials in Physics, Biology …, 2024 - Springer
Subject motion is a long-standing problem of magnetic resonance imaging (MRI), which can
seriously deteriorate the image quality. Various prospective and retrospective methods have …

Probabilistic 4D predictive model from in-room surrogates using conditional generative networks for image-guided radiotherapy

LV Romaguera, T Mezheritsky, R Mansour… - Medical image …, 2021 - Elsevier
Shape and location organ variability induced by respiration constitutes one of the main
challenges during dose delivery in radiotherapy. Providing up-to-date volumetric information …

Real-time non-rigid 3D respiratory motion estimation for MR-guided radiotherapy using MR-MOTUS

NRF Huttinga, T Bruijnen… - … on Medical Imaging, 2021 - ieeexplore.ieee.org
The MR-Linac is a combination of an MR-scanner and radiotherapy linear accelerator
(Linac) which holds the promise to increase the precision of radiotherapy treatments with …

Fast multi-contrast MRI acquisition by optimal sampling of information complementary to pre-acquired MRI contrast

J Yang, XX Li, F Liu, D Nie, P Lio, H Qi… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recent studies on multi-contrast MRI reconstruction have demonstrated the potential of
further accelerating MRI acquisition by exploiting correlation between contrasts. Most of the …

Motion compensated self supervised deep learning for highly accelerated 3D ultrashort Echo time pulmonary MRI

Z Miller, KM Johnson - Magnetic resonance in medicine, 2023 - Wiley Online Library
Purpose To investigate motion compensated, self‐supervised, model based deep learning
(MBDL) as a method to reconstruct free breathing, 3D pulmonary UTE acquisitions. Theory …

Real-time MRI motion estimation through an unsupervised k-space-driven deformable registration network (KS-RegNet)

HC Shao, T Li, MJ Dohopolski, J Wang… - Physics in Medicine …, 2022 - iopscience.iop.org
Purpose. Real-time three-dimensional (3D) magnetic resonance (MR) imaging is
challenging because of slow MR signal acquisition, leading to highly under-sampled k …

[HTML][HTML] Gaussian Processes for real-time 3D motion and uncertainty estimation during MR-guided radiotherapy

NRF Huttinga, T Bruijnen, CAT van den Berg… - Medical Image …, 2023 - Elsevier
Respiratory motion during radiotherapy causes uncertainty in the tumor's location, which is
typically addressed by an increased radiation area and a decreased dose. As a result, the …

Volumetric MRI with sparse sampling for MR‐guided 3D motion tracking via sparse prior‐augmented implicit neural representation learning

L Liu, L Shen, A Johansson, JM Balter, Y Cao… - Medical …, 2024 - Wiley Online Library
Background Volumetric reconstruction of magnetic resonance imaging (MRI) from sparse
samples is desirable for 3D motion tracking and promises to improve magnetic resonance …

Dynamic imaging using motion-compensated smoothness regularization on manifolds (MoCo-SToRM)

Q Zou, LA Torres, SB Fain, NS Higano… - Physics in medicine …, 2022 - iopscience.iop.org
Objective. We introduce an unsupervised motion-compensated reconstruction scheme for
high-resolution free-breathing pulmonary magnetic resonance imaging. Approach. We …