Real‐time radial reconstruction with domain transform manifold learning for MRI‐guided radiotherapy
Background MRI‐guidance techniques that dynamically adapt radiation beams to follow
tumor motion in real time will lead to more accurate cancer treatments and reduced …
tumor motion in real time will lead to more accurate cancer treatments and reduced …
On real-time image reconstruction with neural networks for MRI-guided radiotherapy
MRI-guidance techniques that dynamically adapt radiation beams to follow tumor motion in
real-time will lead to more accurate cancer treatments and reduced collateral healthy tissue …
real-time will lead to more accurate cancer treatments and reduced collateral healthy tissue …
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 …
MR image reconstruction from undersampled data for image-guided radiation therapy using a patient-specific deep manifold image prior
Introduction Recent advancements in radiotherapy (RT) have allowed for the integration of a
Magnetic Resonance (MR) imaging scanner with a medical linear accelerator to use MR …
Magnetic Resonance (MR) imaging scanner with a medical linear accelerator to use MR …
Super-resolution neural networks improve the spatiotemporal resolution of adaptive MRI-guided radiation therapy
Background Magnetic resonance imaging (MRI) offers superb non-invasive, soft tissue
imaging of the human body. However, extensive data sampling requirements severely …
imaging of the human body. However, extensive data sampling requirements severely …
Deep learning-based image reconstruction and motion estimation from undersampled radial k-space for real-time MRI-guided radiotherapy
To enable magnetic resonance imaging (MRI)-guided radiotherapy with real-time
adaptation, motion must be quickly estimated with low latency. The motion estimate is used …
adaptation, motion must be quickly estimated with low latency. The motion estimate is used …
Prior data assisted compressed sensing: a novel MR imaging strategy for real time tracking of lung tumors
Purpose: Hybrid radiotherapy‐MRI devices promise real time tracking of moving tumors to
focus the radiation portals to the tumor during irradiation. This approach will benefit from the …
focus the radiation portals to the tumor during irradiation. This approach will benefit from the …
Deep learning with domain adaptation for accelerated projection‐reconstruction MR
Purpose The radial k‐space trajectory is a well‐established sampling trajectory used in
conjunction with magnetic resonance imaging. However, the radial k‐space trajectory …
conjunction with magnetic resonance imaging. However, the radial k‐space trajectory …
MRI super‐resolution reconstruction for MRI‐guided adaptive radiotherapy using cascaded deep learning: In the presence of limited training data and unknown …
J Chun, H Zhang, HM Gach, S Olberg, T Mazur… - Medical …, 2019 - Wiley Online Library
Purpose Deep learning (DL)‐based super‐resolution (SR) reconstruction for magnetic
resonance imaging (MRI) has recently been receiving attention due to the significant …
resonance imaging (MRI) has recently been receiving attention due to the significant …
[HTML][HTML] Rapid 4D-MRI reconstruction using a deep radial convolutional neural network: Dracula
JN Freedman, OJ Gurney-Champion, S Nill… - Radiotherapy and …, 2021 - Elsevier
Background and Purpose 4D and midposition MRI could inform plan adaptation in lung and
abdominal MR-guided radiotherapy. We present deep learning-based solutions to …
abdominal MR-guided radiotherapy. We present deep learning-based solutions to …